[FreeCourseSite.com] Udemy - Modern Computer Vision™ PyTorch, Tensorflow2 Keras & OpenCV4

磁力链接/BT种子名称

[FreeCourseSite.com] Udemy - Modern Computer Vision™ PyTorch, Tensorflow2 Keras & OpenCV4

磁力链接/BT种子简介

种子哈希：908167937e50d0b36f50e084ad0a1dda4712e8f2
文件大小： 12.75G
已经下载：7487次
下载速度：极快
收录时间：2024-01-02
最近下载：2025-06-01

移花宫入口

移花宫.com邀月.com怜星.com花无缺.comyhgbt.icuyhgbt.top

磁力链接下载

magnet:?xt=urn:btih:908167937E50D0B36F50E084AD0A1DDA4712E8F2
推荐使用PIKPAK网盘下载资源，10TB超大空间，不限制资源，无限次数离线下载，视频在线观看

下载BT种子文件

磁力链接 迅雷下载 PIKPAK在线播放 世界之窗 91视频 含羞草 欲漫涩 逼哩逼哩 成人快手 51品茶 抖阴破解版 极乐禁地 91短视频 TikTok成人版 PornHub 草榴社区 91未成年 乱伦巴士 呦乐园 萝莉岛

最近搜索

文件列表

  • 16. Visualizing What CNN's Learn/6. Filter and Class Maximization.mp4 163.6 MB
  • 18. Building and Loading Advanced CNN Archiectures and Rank-N Accuracy/2. Loading Pre-trained Networks in PyTorch (ResNets, DenseNets, MobileNET, VGG19).mp4 161.2 MB
  • 2. Download Code and Setup Colab/1.1 Code - Modern Computer Vision_05_06_2022.zip 158.3 MB
  • 9. OpenCV Projects/6. Neural Style Transfer with OpenCV.mp4 150.0 MB
  • 22. Google DeepStream and Neural Style Transfer/5. Neural Style Transfer in Keras.mp4 147.9 MB
  • 4. OpenCV - Image Segmentation/2. Moments, Sorting, Approximating and Matching Contours.mp4 146.6 MB
  • 18. Building and Loading Advanced CNN Archiectures and Rank-N Accuracy/1. Implementing LeNet and AlexNet in Keras.mp4 146.1 MB
  • 26. Face Recognition (Age, Gender, Emotion and Ethnicity) with Deep Learning/5. DeepFace - Age, Gender, Emotion, Ethnicity and Face Recognition.mp4 138.8 MB
  • 21. Transfer Learning and Fine Tuning/4. Keras Feature Extraction.mp4 138.2 MB
  • 29. Gun Detector - Scaled-YoloV4/1. Gun Detector - Scaled-YoloV4.mp4 134.7 MB
  • 21. Transfer Learning and Fine Tuning/5. PyTorch Fine Tuning.mp4 127.5 MB
  • 2. Download Code and Setup Colab/1.2 ebook slides - Modern Computer Vision.pdf 127.5 MB
  • 9. OpenCV Projects/3. OCR with PyTesseract and EasyOCR (Text Detection).mp4 125.3 MB
  • 3. OpenCV - Image Operations/9. Thresholding, Binarization & Adaptive Thresholding.mp4 122.9 MB
  • 4. OpenCV - Image Segmentation/1. Contours - Drawing, Hierarchy and Modes.mp4 122.8 MB
  • 19. Using Callbacks in Keras and PyTorch/2. Cats vs Dogs Classifier using Callbacks in PyTorch.mp4 120.6 MB
  • 3. OpenCV - Image Operations/6. Scaling, Re-sizing, Interpolations and Cropping.mp4 120.5 MB
  • 19. Using Callbacks in Keras and PyTorch/3. Cats vs Dogs Classifier using Callbacks in Keras.mp4 120.3 MB
  • 18. Building and Loading Advanced CNN Archiectures and Rank-N Accuracy/3. Loading Pre-trained Networks in Keras (ResNets, DenseNets, MobileNET, VGG19).mp4 116.8 MB
  • 5. OpenCV - Haar Cascade Classifiers/1. Face and Eye Detection with Haar Cascade Classifiers.mp4 115.6 MB
  • 24. Generative Adversarial Networks (GANs)/4. Use Cases for GANs.mp4 113.4 MB
  • 15. Improving Models and Advanced CNN Design/12. Training a Fashion Classifider (FNIST) with Regularization using PyTorch.mp4 113.3 MB
  • 16. Visualizing What CNN's Learn/3. Keras Filter Visualization and Activations.mp4 112.4 MB
  • 20. PyTorch Lightning/3. Auto Batch and Learning Rate Selection plus Tensorboards.mp4 111.7 MB
  • 21. Transfer Learning and Fine Tuning/7. PyTorch Feature Extraction.mp4 108.4 MB
  • 12. Building CNNs in PyTorch/5. Building our Model.mp4 107.3 MB
  • 24. Generative Adversarial Networks (GANs)/7. Super Resolution GAN.mp4 107.2 MB
  • 24. Generative Adversarial Networks (GANs)/5. Keras DCGAN with MNIST.mp4 105.8 MB
  • 18. Building and Loading Advanced CNN Archiectures and Rank-N Accuracy/5. Getting the Rank-N Accuracy in PyTorch.mp4 102.7 MB
  • 48. Image Captioning with Keras/1. Image Captioning with Keras.mp4 100.8 MB
  • 12. Building CNNs in PyTorch/7. Training Your Model.mp4 100.7 MB
  • 15. Improving Models and Advanced CNN Design/10. Training a Fashion Classifider (FNIST) with Regularization using Keras.mp4 100.7 MB
  • 21. Transfer Learning and Fine Tuning/3. Transfer Learning and Fine Tuning with Keras.mp4 100.7 MB
  • 7. OpenCV - Motion and Object Tracking/2. Object Tracking with Optical Flow.mp4 99.8 MB
  • 3. OpenCV - Image Operations/1. Getting Started with OpenCV4.mp4 99.3 MB
  • 52. Point Cloud Segmentation Using PointNet/1. Point Cloud Segmentation Using PointNet.mp4 96.5 MB
  • 55. Low Light Image Enhancement MIRNet/1. Low Light Image Enhancement MIRNet.mp4 96.0 MB
  • 9. OpenCV Projects/10. Add and Remove Noise and Fix Contrast with Histogram Equalization.mp4 93.3 MB
  • 5. OpenCV - Haar Cascade Classifiers/2. Vehicle and Pedestrian Detection.mp4 90.3 MB
  • 31. Sign Language Detector TFODAPI EfficentDet/1. Sign Language Detector TFODAPI EfficentDet.mp4 89.3 MB
  • 9. OpenCV Projects/12. Facial Recognition.mp4 88.4 MB
  • 1. Introduction/1. Course Introduction.mp4 87.0 MB
  • 15. Improving Models and Advanced CNN Design/9. Training a Fashion Classifider (FNIST) with no Regularization using Keras.mp4 86.7 MB
  • 30. Mask Detector TFODAPI MobileNetV2_SSD/1. Mask Detector TFODAPI MobileNetV2_SSD.mp4 85.1 MB
  • 9. OpenCV Projects/8. Colorize Black and White Photos using a Caffe Model in OpenCV.mp4 84.9 MB
  • 26. Face Recognition (Age, Gender, Emotion and Ethnicity) with Deep Learning/3. Face Recognition Keras One Shot Learning and Friends.mp4 84.5 MB
  • 23. Autoencoders/2. Autoencoders in Keras.mp4 84.5 MB
  • 16. Visualizing What CNN's Learn/8. Grad-CAM Plus.mp4 84.3 MB
  • 3. OpenCV - Image Operations/10. Dilation, Erosion and Edge Detection.mp4 83.8 MB
  • 6. OpenCV - Image Analysis and Transformation/2. Histograms and K-Means Clustering for Dominant Colors.mp4 83.8 MB
  • 9. OpenCV Projects/5. YOLOv3 in OpenCV.mp4 83.4 MB
  • 40. Deep Segmentation - U-Net, SegNet, DeeplabV3 and Mask R-CNN/1. Introduction to Deep Segmentation.mp4 82.0 MB
  • 46. Depth Estimation/1. Depth Estimation Project.mp4 80.5 MB
  • 44. Vision Transformers - ViTs/2. Vision Transformer in Detail with PyTorch.mp4 79.9 MB
  • 13. Building CNNs in TensorFlow with Keras/7. Saving and Loading and Visualising Results.mp4 79.2 MB
  • 40. Deep Segmentation - U-Net, SegNet, DeeplabV3 and Mask R-CNN/2. Image Segmentation Keras UNET SegNet.mp4 76.6 MB
  • 25. Siamese Network/3. Siamese Networks in Keras.mp4 76.6 MB
  • 22. Google DeepStream and Neural Style Transfer/2. Google DeepDream in Keras.mp4 76.4 MB
  • 20. PyTorch Lightning/4. PyTorch Lightning Calls, Saving, Inference.mp4 75.1 MB
  • 39. Plant Doctor Detector YOLOv5/1. Plant Doctor Detector YOLOv5.mp4 74.6 MB
  • 7. OpenCV - Motion and Object Tracking/1. Motion Tracking with Mean Shift and CAMSHIFT.mp4 74.5 MB
  • 40. Deep Segmentation - U-Net, SegNet, DeeplabV3 and Mask R-CNN/5. Detectron2 Mask R-CNN.mp4 74.3 MB
  • 12. Building CNNs in PyTorch/3. Inspect and Visualise Data.mp4 74.0 MB
  • 9. OpenCV Projects/4. Barcode, QR Generation and Reading.mp4 72.0 MB
  • 4. OpenCV - Image Segmentation/4. Counting Circles, Ellipses and Finding Waldo with Template Matching.mp4 71.8 MB
  • 3. OpenCV - Image Operations/3. Colour Spaces - RGB and HSV.mp4 71.6 MB
  • 14. Assessing Model Performance/1. Deep Learning Libraries PyTorch vs Keras Review.mp4 71.5 MB
  • 25. Siamese Network/4. Siamese Networks in PyTorch.mp4 71.2 MB
  • 14. Assessing Model Performance/3. Confusion Matrix and Classification Report.mp4 70.9 MB
  • 3. OpenCV - Image Operations/5. Transformations - Translations and Rotations.mp4 70.5 MB
  • 10. OpenCV - Working With Video/1. Using Your Webcam and Creating a Live Sketch of Yourself.mp4 69.8 MB
  • 3. OpenCV - Image Operations/7. Arithmetic and Bitwise Operations.mp4 69.4 MB
  • 6. OpenCV - Image Analysis and Transformation/6. Background and Foreground Subtraction.mp4 69.3 MB
  • 23. Autoencoders/3. Autoencoders in PyTorch.mp4 69.3 MB
  • 24. Generative Adversarial Networks (GANs)/6. PyTorch GANs.mp4 68.6 MB
  • 27. Object Detection/1. Object Detection.mp4 68.4 MB
  • 33. Mushroom Detector Detectron2/1. Mushroom Detector Detectron2.mp4 68.1 MB
  • 14. Assessing Model Performance/4. Keras Viewing Misclassifications.mp4 68.1 MB
  • 10. OpenCV - Working With Video/7. Importing YouTube Videos into OpenCV.mp4 68.0 MB
  • 13. Building CNNs in TensorFlow with Keras/4. Constructing the CNN.mp4 67.6 MB
  • 6. OpenCV - Image Analysis and Transformation/1. Perspective Transforms.mp4 67.6 MB
  • 15. Improving Models and Advanced CNN Design/11. Training a Fashion Classifider (FNIST) with no Regularization using PyTorch.mp4 67.3 MB
  • 20. PyTorch Lightning/5. Training on Multiple GPU, Profiling and TPUs.mp4 67.3 MB
  • 1. Introduction/2. Course Overview.mp4 66.9 MB
  • 20. PyTorch Lightning/2. Lightning Setup and Class.mp4 65.2 MB
  • 40. Deep Segmentation - U-Net, SegNet, DeeplabV3 and Mask R-CNN/4. Mask-RCNN Tensorflow Matterport.mp4 64.7 MB
  • 53. Medical Project - X-Ray Pneumonia Prediction/1. X-Ray Pneumonia Prediction.mp4 64.4 MB
  • 54. Medical Project - 3D CT Scan Classification/1. 3D CT Scan Classification.mp4 63.2 MB
  • 40. Deep Segmentation - U-Net, SegNet, DeeplabV3 and Mask R-CNN/3. PyTorch DeepLabV3.mp4 63.1 MB
  • 42. Tracking with DeepSORT/1. DeepSORT Introduction.mp4 62.4 MB
  • 51. Point Cloud Classification PointNet/1. Point Cloud Classification PointNet.mp4 62.4 MB
  • 32. Pothole Detector - TinyYOLOv4/1. Pothole Detector - TinyYOLOv4.mp4 62.4 MB
  • 11. Deep Learning in Computer Vision Introduction/22. Deep Learning Libraries Overview.mp4 61.9 MB
  • 9. OpenCV Projects/1. Tilt Shift Effects.mp4 61.9 MB
  • 3. OpenCV - Image Operations/8. Convolutions, Blurring and Sharpening Images.mp4 61.8 MB
  • 43. Deep Fakes/1. Creating a Deep Fake.mp4 61.5 MB
  • 45. BiT BigTransfer Classifier Keras/1. BiT BigTransfer Classifier Keras.mp4 61.5 MB
  • 37. Bloodcell Detector YOLOv5/1. Bloodcell Detector YOLOv5.mp4 61.4 MB
  • 42. Tracking with DeepSORT/2. DeepSORT with YOLOv5.mp4 61.2 MB
  • 22. Google DeepStream and Neural Style Transfer/3. Google DeepDream in PyTorch.mp4 61.2 MB
  • 22. Google DeepStream and Neural Style Transfer/6. Neural Style Transfer in PyTorch.mp4 60.7 MB
  • 11. Deep Learning in Computer Vision Introduction/21. Deep Learning History.mp4 60.3 MB
  • 35. Drone Maritime Detector R-CNN/1. Drone Maritime Detector R-CNN.mp4 59.6 MB
  • 49. Video Classification usign CNN+RNN/1. Video Classification usign CNN+RNN.mp4 59.5 MB
  • 26. Face Recognition (Age, Gender, Emotion and Ethnicity) with Deep Learning/2. Facial Similarity Keras VGGFace.mp4 59.4 MB
  • 4. OpenCV - Image Segmentation/3. Line, Circle and Blob Detection.mp4 59.3 MB
  • 47. Image Similarity using Metric Learning/1. Image Similarity using Metric Learning.mp4 58.7 MB
  • 21. Transfer Learning and Fine Tuning/2. Transfer Learning in PyTorch Lightning.mp4 58.6 MB
  • 18. Building and Loading Advanced CNN Archiectures and Rank-N Accuracy/6. Getting the Rank-N Accuracy in Keras.mp4 58.6 MB
  • 40. Deep Segmentation - U-Net, SegNet, DeeplabV3 and Mask R-CNN/6. Train Mask R-CNN Shapes Dataset.mp4 57.6 MB
  • 56. Deploy your CV App using Flask RestFUL API & Web App/1. Flask RestFUL API.mp4 57.6 MB
  • 27. Object Detection/2. History of Object Detectors.mp4 55.4 MB
  • 3. OpenCV - Image Operations/2. Grayscaling Images.mp4 55.1 MB
  • 3. OpenCV - Image Operations/4. Drawing on Images.mp4 54.6 MB
  • 9. OpenCV Projects/7. SSDs in OpenCV.mp4 54.3 MB
  • 14. Assessing Model Performance/6. PyTorch Viewing Misclassifications.mp4 53.9 MB
  • 26. Face Recognition (Age, Gender, Emotion and Ethnicity) with Deep Learning/4. Face Recognition PyTorch FaceNet.mp4 53.8 MB
  • 22. Google DeepStream and Neural Style Transfer/4. Introduction to Neural Style Transfer.mp4 52.4 MB
  • 34. Website Region Detector YOLOv4 Darknet/1. Website Region Detector YOLOv4 Darknet.mp4 52.0 MB
  • 8. OpenCV - Facial Landmark Detection & Face Swaps/2. Face Swapping with Dlib.mp4 51.8 MB
  • 24. Generative Adversarial Networks (GANs)/3. Training GANs.mp4 51.7 MB
  • 12. Building CNNs in PyTorch/8. Saving Model and Displaying Results.mp4 51.7 MB
  • 50. Video Classification with Transformers/1. Video Classification with Transformers.mp4 51.6 MB
  • 7. OpenCV - Motion and Object Tracking/3. Simple Object Tracking by Color.mp4 51.0 MB
  • 44. Vision Transformers - ViTs/3. Vision Transformers in Keras.mp4 50.3 MB
  • 12. Building CNNs in PyTorch/1. Importing Required Libraries.mp4 50.0 MB
  • 57. OCR Captcha Cracker/1. OCR Captcha Cracker.mp4 48.6 MB
  • 10. OpenCV - Working With Video/6. Capturing Video using Screenshots.mp4 48.6 MB
  • 41. Body Pose Estimation/1. Body Pose Estimation.mp4 48.5 MB
  • 1. Introduction/3. What Makes Computer Vision Hard.mp4 48.4 MB
  • 27. Object Detection/4. Mean Average Precision.mp4 47.9 MB
  • 9. OpenCV Projects/2. GrabCut Algorithm for Background Removal.mp4 47.9 MB
  • 13. Building CNNs in TensorFlow with Keras/5. Training the Model.mp4 47.7 MB
  • 1. Introduction/4. What are Images.mp4 46.4 MB
  • 15. Improving Models and Advanced CNN Design/1. What is Overfitting and Generalisation.mp4 46.2 MB
  • 17. Advamced Convolutional Neural Networks/7. MobileNetV1 and V2.mp4 46.0 MB
  • 24. Generative Adversarial Networks (GANs)/1. Introduction to GANs.mp4 45.7 MB
  • 14. Assessing Model Performance/5. Keras - Confusion Matrix and Classification Report.mp4 45.5 MB
  • 6. OpenCV - Image Analysis and Transformation/5. Watershed Algorithm Marker-Dased Image Segmentation.mp4 45.4 MB
  • 36. Chess Piece YOLOv3/1. Chess Piece YOLOv3.mp4 44.7 MB
  • 6. OpenCV - Image Analysis and Transformation/3. Comparing Images MSE and Structual Similarity.mp4 44.1 MB
  • 10. OpenCV - Working With Video/4. Video Streams and CCTV - RTSP and IP.mp4 44.1 MB
  • 27. Object Detection/6. R-CNNs, Fast R-CNNs and Faster R-CNNs.mp4 43.2 MB
  • 11. Deep Learning in Computer Vision Introduction/19. Optimisers and Learning Rate Schedules.mp4 42.9 MB
  • 6. OpenCV - Image Analysis and Transformation/4. Filtering on Colour.mp4 42.9 MB
  • 28. Modern Object Detectors - YOLO, EfficientDet, Detectron2/6. Detectron2.mp4 42.6 MB
  • 22. Google DeepStream and Neural Style Transfer/1. Introduction to Google DeepDream Visualizations.mp4 41.8 MB
  • 9. OpenCV Projects/11. Detect Blur in Images.mp4 41.5 MB
  • 20. PyTorch Lightning/1. Introduction to PyTorch Lightning.mp4 40.1 MB
  • 8. OpenCV - Facial Landmark Detection & Face Swaps/1. Facial Landmark Detection with Dlib.mp4 39.4 MB
  • 56. Deploy your CV App using Flask RestFUL API & Web App/2. Flask Web App.mp4 39.1 MB
  • 4. OpenCV - Image Segmentation/5. Finding Corners.mp4 38.3 MB
  • 13. Building CNNs in TensorFlow with Keras/6. Plotting the Training Results.mp4 38.2 MB
  • 11. Deep Learning in Computer Vision Introduction/20. Deep Learning CNN Recap.mp4 38.2 MB
  • 10. OpenCV - Working With Video/5. Auto Reconnect to Video Streams.mp4 38.0 MB
  • 10. OpenCV - Working With Video/3. Saving or Recording Videos in OpenCV.mp4 37.5 MB
  • 16. Visualizing What CNN's Learn/2. Visualising Filter Activations.mp4 37.3 MB
  • 24. Generative Adversarial Networks (GANs)/8. AnimeGAN.mp4 36.5 MB
  • 10. OpenCV - Working With Video/2. Opening Video Files in OpenCV.mp4 35.6 MB
  • 11. Deep Learning in Computer Vision Introduction/2. Convolutions.mp4 35.5 MB
  • 13. Building CNNs in TensorFlow with Keras/3. Preprocessing Our Data.mp4 35.2 MB
  • 28. Modern Object Detectors - YOLO, EfficientDet, Detectron2/1. Introduction to YOLO.mp4 35.1 MB
  • 11. Deep Learning in Computer Vision Introduction/18. Gradient Descent.mp4 34.5 MB
  • 26. Face Recognition (Age, Gender, Emotion and Ethnicity) with Deep Learning/1. Face Recognition Overview.mp4 33.6 MB
  • 17. Advamced Convolutional Neural Networks/11. DenseNet.mp4 33.6 MB
  • 15. Improving Models and Advanced CNN Design/5. Data Augmentation.mp4 33.4 MB
  • 21. Transfer Learning and Fine Tuning/1. Transfer Learning Introduction.mp4 33.4 MB
  • 24. Generative Adversarial Networks (GANs)/9. ArcaneGAN.mp4 33.1 MB
  • 27. Object Detection/7. Single Shot Detectors (SSDs).mp4 32.4 MB
  • 28. Modern Object Detectors - YOLO, EfficientDet, Detectron2/5. EfficientDet.mp4 32.2 MB
  • 38. Hard Hat Detector EfficentDet/1. Hard Hat Detector EfficentDet.mp4 32.1 MB
  • 16. Visualizing What CNN's Learn/5. Class Maximization.mp4 31.6 MB
  • 12. Building CNNs in PyTorch/4. Data Loaders.mp4 31.4 MB
  • 12. Building CNNs in PyTorch/2. Transformation Pipeline.mp4 31.0 MB
  • 17. Advamced Convolutional Neural Networks/12. The ImageNet Dataset.mp4 31.0 MB
  • 13. Building CNNs in TensorFlow with Keras/2. View and Inspect Data.mp4 30.9 MB
  • 11. Deep Learning in Computer Vision Introduction/12. Putting Together Your Convolutional Neural Network.mp4 30.8 MB
  • 28. Modern Object Detectors - YOLO, EfficientDet, Detectron2/2. How YOLO Works.mp4 30.7 MB
  • 14. Assessing Model Performance/7. PyTorch - Confusion Matrix and Misclassifications.mp4 30.7 MB
  • 11. Deep Learning in Computer Vision Introduction/17. Backpropagation.mp4 30.4 MB
  • 24. Generative Adversarial Networks (GANs)/1.1 Slides - Generative Adverserial Networks.pdf 30.3 MB
  • 21. Transfer Learning and Fine Tuning/6. PyTorch Transfer Learning and Freezing Network Layers.mp4 30.2 MB
  • 25. Siamese Network/1. Introduction to Siamese Networks.mp4 30.2 MB
  • 9. OpenCV Projects/9. Inpainting to Restore Damaged Photos.mp4 29.9 MB
  • 11. Deep Learning in Computer Vision Introduction/15. Training a CNN.mp4 28.7 MB
  • 44. Vision Transformers - ViTs/1. Introduction to Vision Transformers.mp4 28.0 MB
  • 13. Building CNNs in TensorFlow with Keras/1. Loading Data.mp4 28.0 MB
  • 24. Generative Adversarial Networks (GANs)/2. How Do GANs Work.mp4 27.8 MB
  • 12. Building CNNs in PyTorch/9. Plot and Visualize Your Results.mp4 27.1 MB
  • 23. Autoencoders/1. Introduction to Autoencoders.mp4 26.6 MB
  • 28. Modern Object Detectors - YOLO, EfficientDet, Detectron2/3. Training YOLO.mp4 26.2 MB
  • 17. Advamced Convolutional Neural Networks/10. EfficientNet.mp4 26.2 MB
  • 11. Deep Learning in Computer Vision Introduction/16. Loss Functions.mp4 26.1 MB
  • 28. Modern Object Detectors - YOLO, EfficientDet, Detectron2/4. YOLO Evolution.mp4 25.4 MB
  • 11. Deep Learning in Computer Vision Introduction/3. Feature Detectors.mp4 25.0 MB
  • 15. Improving Models and Advanced CNN Design/7. Batch Normalization.mp4 25.0 MB
  • 11. Deep Learning in Computer Vision Introduction/13. Parameter Counts in CNNs.mp4 25.0 MB
  • 11. Deep Learning in Computer Vision Introduction/9. Pooling.mp4 24.6 MB
  • 17. Advamced Convolutional Neural Networks/8. InceptionV3.mp4 24.6 MB
  • 17. Advamced Convolutional Neural Networks/6. Why ResNets Work So Well.mp4 24.4 MB
  • 17. Advamced Convolutional Neural Networks/9. SqueezeNet.mp4 24.3 MB
  • 16. Visualizing What CNN's Learn/4. Maximizing Filters.mp4 24.2 MB
  • 17. Advamced Convolutional Neural Networks/4. VGG16 and VGG19.mp4 24.2 MB
  • 14. Assessing Model Performance/2. Assessing Model Performance.mp4 23.7 MB
  • 2. Download Code and Setup Colab/2. Setup - Download Code and Configure Colab.mp4 23.7 MB
  • 11. Deep Learning in Computer Vision Introduction/8. Activation Functions.mp4 22.8 MB
  • 11. Deep Learning in Computer Vision Introduction/14. Why CNNs Work So Well On Images.mp4 21.5 MB
  • 16. Visualizing What CNN's Learn/1. Visualizing CNN Filters or Feature Maps.mp4 21.5 MB
  • 27. Object Detection/5. Non Maximum Suppression.mp4 20.5 MB
  • 17. Advamced Convolutional Neural Networks/2. LeNet.mp4 19.6 MB
  • 17. Advamced Convolutional Neural Networks/5. ResNets.mp4 18.7 MB
  • 17. Advamced Convolutional Neural Networks/3. AlexNet.mp4 18.4 MB
  • 27. Object Detection/3. Intersection Over Union.mp4 18.3 MB
  • 11. Deep Learning in Computer Vision Introduction/7. Stride.mp4 18.0 MB
  • 11. Deep Learning in Computer Vision Introduction/4. 3D Convolutions and Color Images.mp4 17.4 MB
  • 19. Using Callbacks in Keras and PyTorch/1. What are Callbacks.mp4 17.0 MB
  • 11. Deep Learning in Computer Vision Introduction/1. Introduction to Convolution Neural Networks.mp4 16.6 MB
  • 15. Improving Models and Advanced CNN Design/4. L1 and L2 Regularization.mp4 16.4 MB
  • 16. Visualizing What CNN's Learn/7. Grad-CAM Visualize What Influences Your Model.mp4 15.6 MB
  • 12. Building CNNs in PyTorch/6. Optimisers and Loss Function.mp4 15.6 MB
  • 11. Deep Learning in Computer Vision Introduction/6. Padding.mp4 14.9 MB
  • 11. Deep Learning in Computer Vision Introduction/5. Kernel Size and Depth.mp4 14.3 MB
  • 25. Siamese Network/2. Training Siamese Networks.mp4 14.0 MB
  • 15. Improving Models and Advanced CNN Design/3. Drop Out.mp4 13.7 MB
  • 15. Improving Models and Advanced CNN Design/6. Early Stopping.mp4 13.6 MB
  • 18. Building and Loading Advanced CNN Archiectures and Rank-N Accuracy/4. The Top-N or Rank-N Accuracy Metric.mp4 13.0 MB
  • 15. Improving Models and Advanced CNN Design/8. When Do We Use Regularization.mp4 12.1 MB
  • 11. Deep Learning in Computer Vision Introduction/10. Fully Connected Layers.mp4 11.9 MB
  • 17. Advamced Convolutional Neural Networks/1. History and Evolution of Convolutional Neural Networks.mp4 9.6 MB
  • 11. Deep Learning in Computer Vision Introduction/11. Softmax.mp4 9.3 MB
  • 15. Improving Models and Advanced CNN Design/2. Introduction to Regularization.mp4 8.4 MB
  • 18. Building and Loading Advanced CNN Archiectures and Rank-N Accuracy/2. Loading Pre-trained Networks in PyTorch (ResNets, DenseNets, MobileNET, VGG19).srt 29.6 kB
  • 16. Visualizing What CNN's Learn/6. Filter and Class Maximization.srt 25.4 kB
  • 4. OpenCV - Image Segmentation/2. Moments, Sorting, Approximating and Matching Contours.srt 25.4 kB
  • 18. Building and Loading Advanced CNN Archiectures and Rank-N Accuracy/1. Implementing LeNet and AlexNet in Keras.srt 23.8 kB
  • 3. OpenCV - Image Operations/1. Getting Started with OpenCV4.srt 23.6 kB
  • 19. Using Callbacks in Keras and PyTorch/2. Cats vs Dogs Classifier using Callbacks in PyTorch.srt 23.4 kB
  • 22. Google DeepStream and Neural Style Transfer/5. Neural Style Transfer in Keras.srt 22.8 kB
  • 19. Using Callbacks in Keras and PyTorch/3. Cats vs Dogs Classifier using Callbacks in Keras.srt 22.8 kB
  • 16. Visualizing What CNN's Learn/3. Keras Filter Visualization and Activations.srt 22.6 kB
  • 21. Transfer Learning and Fine Tuning/5. PyTorch Fine Tuning.srt 22.2 kB
  • 4. OpenCV - Image Segmentation/1. Contours - Drawing, Hierarchy and Modes.srt 20.9 kB
  • 14. Assessing Model Performance/3. Confusion Matrix and Classification Report.srt 20.9 kB
  • 26. Face Recognition (Age, Gender, Emotion and Ethnicity) with Deep Learning/5. DeepFace - Age, Gender, Emotion, Ethnicity and Face Recognition.srt 20.5 kB
  • 11. Deep Learning in Computer Vision Introduction/21. Deep Learning History.srt 20.5 kB
  • 18. Building and Loading Advanced CNN Archiectures and Rank-N Accuracy/3. Loading Pre-trained Networks in Keras (ResNets, DenseNets, MobileNET, VGG19).srt 20.0 kB
  • 21. Transfer Learning and Fine Tuning/4. Keras Feature Extraction.srt 19.9 kB
  • 14. Assessing Model Performance/1. Deep Learning Libraries PyTorch vs Keras Review.srt 19.5 kB
  • 3. OpenCV - Image Operations/6. Scaling, Re-sizing, Interpolations and Cropping.srt 19.4 kB
  • 9. OpenCV Projects/3. OCR with PyTesseract and EasyOCR (Text Detection).srt 19.3 kB
  • 3. OpenCV - Image Operations/9. Thresholding, Binarization & Adaptive Thresholding.srt 19.2 kB
  • 12. Building CNNs in PyTorch/5. Building our Model.srt 18.8 kB
  • 15. Improving Models and Advanced CNN Design/12. Training a Fashion Classifider (FNIST) with Regularization using PyTorch.srt 18.4 kB
  • 12. Building CNNs in PyTorch/7. Training Your Model.srt 18.2 kB
  • 5. OpenCV - Haar Cascade Classifiers/1. Face and Eye Detection with Haar Cascade Classifiers.srt 18.2 kB
  • 29. Gun Detector - Scaled-YoloV4/1. Gun Detector - Scaled-YoloV4.srt 18.2 kB
  • 15. Improving Models and Advanced CNN Design/10. Training a Fashion Classifider (FNIST) with Regularization using Keras.srt 17.7 kB
  • 1. Introduction/1. Course Introduction.srt 17.6 kB
  • 21. Transfer Learning and Fine Tuning/3. Transfer Learning and Fine Tuning with Keras.srt 17.6 kB
  • 20. PyTorch Lightning/3. Auto Batch and Learning Rate Selection plus Tensorboards.srt 17.5 kB
  • 9. OpenCV Projects/6. Neural Style Transfer with OpenCV.srt 17.2 kB
  • 40. Deep Segmentation - U-Net, SegNet, DeeplabV3 and Mask R-CNN/1. Introduction to Deep Segmentation.srt 17.1 kB
  • 24. Generative Adversarial Networks (GANs)/5. Keras DCGAN with MNIST.srt 16.8 kB
  • 18. Building and Loading Advanced CNN Archiectures and Rank-N Accuracy/5. Getting the Rank-N Accuracy in PyTorch.srt 16.8 kB
  • 1. Introduction/2. Course Overview.srt 16.6 kB
  • 13. Building CNNs in TensorFlow with Keras/7. Saving and Loading and Visualising Results.srt 16.3 kB
  • 11. Deep Learning in Computer Vision Introduction/22. Deep Learning Libraries Overview.srt 16.3 kB
  • 21. Transfer Learning and Fine Tuning/7. PyTorch Feature Extraction.srt 16.2 kB
  • 6. OpenCV - Image Analysis and Transformation/2. Histograms and K-Means Clustering for Dominant Colors.srt 16.0 kB
  • 7. OpenCV - Motion and Object Tracking/2. Object Tracking with Optical Flow.srt 15.9 kB
  • 17. Advamced Convolutional Neural Networks/7. MobileNetV1 and V2.srt 15.1 kB
  • 5. OpenCV - Haar Cascade Classifiers/2. Vehicle and Pedestrian Detection.srt 15.0 kB
  • 22. Google DeepStream and Neural Style Transfer/4. Introduction to Neural Style Transfer.srt 14.9 kB
  • 3. OpenCV - Image Operations/7. Arithmetic and Bitwise Operations.srt 14.9 kB
  • 9. OpenCV Projects/12. Facial Recognition.srt 14.8 kB
  • 3. OpenCV - Image Operations/4. Drawing on Images.srt 14.8 kB
  • 3. OpenCV - Image Operations/10. Dilation, Erosion and Edge Detection.srt 14.8 kB
  • 11. Deep Learning in Computer Vision Introduction/20. Deep Learning CNN Recap.srt 14.6 kB
  • 15. Improving Models and Advanced CNN Design/9. Training a Fashion Classifider (FNIST) with no Regularization using Keras.srt 14.6 kB
  • 48. Image Captioning with Keras/1. Image Captioning with Keras.srt 14.4 kB
  • 3. OpenCV - Image Operations/5. Transformations - Translations and Rotations.srt 14.3 kB
  • 9. OpenCV Projects/10. Add and Remove Noise and Fix Contrast with Histogram Equalization.srt 14.1 kB
  • 23. Autoencoders/2. Autoencoders in Keras.srt 14.0 kB
  • 24. Generative Adversarial Networks (GANs)/7. Super Resolution GAN.srt 13.9 kB
  • 24. Generative Adversarial Networks (GANs)/4. Use Cases for GANs.srt 13.7 kB
  • 52. Point Cloud Segmentation Using PointNet/1. Point Cloud Segmentation Using PointNet.srt 13.5 kB
  • 9. OpenCV Projects/4. Barcode, QR Generation and Reading.srt 13.4 kB
  • 27. Object Detection/1. Object Detection.srt 13.4 kB
  • 16. Visualizing What CNN's Learn/8. Grad-CAM Plus.srt 13.4 kB
  • 15. Improving Models and Advanced CNN Design/1. What is Overfitting and Generalisation.srt 13.3 kB
  • 11. Deep Learning in Computer Vision Introduction/2. Convolutions.srt 13.3 kB
  • 20. PyTorch Lightning/4. PyTorch Lightning Calls, Saving, Inference.srt 13.3 kB
  • 25. Siamese Network/3. Siamese Networks in Keras.srt 13.1 kB
  • 6. OpenCV - Image Analysis and Transformation/1. Perspective Transforms.srt 13.0 kB
  • 21. Transfer Learning and Fine Tuning/1. Transfer Learning Introduction.srt 13.0 kB
  • 12. Building CNNs in PyTorch/3. Inspect and Visualise Data.srt 12.9 kB
  • 9. OpenCV Projects/5. YOLOv3 in OpenCV.srt 12.8 kB
  • 42. Tracking with DeepSORT/1. DeepSORT Introduction.srt 12.7 kB
  • 3. OpenCV - Image Operations/3. Colour Spaces - RGB and HSV.srt 12.5 kB
  • 27. Object Detection/2. History of Object Detectors.srt 12.4 kB
  • 44. Vision Transformers - ViTs/2. Vision Transformer in Detail with PyTorch.srt 12.4 kB
  • 20. PyTorch Lightning/1. Introduction to PyTorch Lightning.srt 12.3 kB
  • 27. Object Detection/4. Mean Average Precision.srt 12.0 kB
  • 16. Visualizing What CNN's Learn/2. Visualising Filter Activations.srt 11.8 kB
  • 10. OpenCV - Working With Video/1. Using Your Webcam and Creating a Live Sketch of Yourself.srt 11.8 kB
  • 11. Deep Learning in Computer Vision Introduction/18. Gradient Descent.srt 11.8 kB
  • 9. OpenCV Projects/8. Colorize Black and White Photos using a Caffe Model in OpenCV.srt 11.8 kB
  • 14. Assessing Model Performance/4. Keras Viewing Misclassifications.srt 11.7 kB
  • 24. Generative Adversarial Networks (GANs)/6. PyTorch GANs.srt 11.7 kB
  • 40. Deep Segmentation - U-Net, SegNet, DeeplabV3 and Mask R-CNN/2. Image Segmentation Keras UNET SegNet.srt 11.5 kB
  • 11. Deep Learning in Computer Vision Introduction/12. Putting Together Your Convolutional Neural Network.srt 11.5 kB
  • 23. Autoencoders/3. Autoencoders in PyTorch.srt 11.5 kB
  • 27. Object Detection/6. R-CNNs, Fast R-CNNs and Faster R-CNNs.srt 11.5 kB
  • 6. OpenCV - Image Analysis and Transformation/6. Background and Foreground Subtraction.srt 11.5 kB
  • 30. Mask Detector TFODAPI MobileNetV2_SSD/1. Mask Detector TFODAPI MobileNetV2_SSD.srt 11.4 kB
  • 26. Face Recognition (Age, Gender, Emotion and Ethnicity) with Deep Learning/3. Face Recognition Keras One Shot Learning and Friends.srt 11.3 kB
  • 24. Generative Adversarial Networks (GANs)/3. Training GANs.srt 11.2 kB
  • 1. Introduction/4. What are Images.srt 11.0 kB
  • 46. Depth Estimation/1. Depth Estimation Project.srt 11.0 kB
  • 55. Low Light Image Enhancement MIRNet/1. Low Light Image Enhancement MIRNet.srt 10.9 kB
  • 12. Building CNNs in PyTorch/8. Saving Model and Displaying Results.srt 10.9 kB
  • 7. OpenCV - Motion and Object Tracking/1. Motion Tracking with Mean Shift and CAMSHIFT.srt 10.8 kB
  • 15. Improving Models and Advanced CNN Design/11. Training a Fashion Classifider (FNIST) with no Regularization using PyTorch.srt 10.8 kB
  • 31. Sign Language Detector TFODAPI EfficentDet/1. Sign Language Detector TFODAPI EfficentDet.srt 10.8 kB
  • 22. Google DeepStream and Neural Style Transfer/2. Google DeepDream in Keras.srt 10.8 kB
  • 26. Face Recognition (Age, Gender, Emotion and Ethnicity) with Deep Learning/1. Face Recognition Overview.srt 10.8 kB
  • 23. Autoencoders/1. Introduction to Autoencoders.srt 10.7 kB
  • 12. Building CNNs in PyTorch/1. Importing Required Libraries.srt 10.7 kB
  • 17. Advamced Convolutional Neural Networks/11. DenseNet.srt 10.7 kB
  • 11. Deep Learning in Computer Vision Introduction/19. Optimisers and Learning Rate Schedules.srt 10.3 kB
  • 56. Deploy your CV App using Flask RestFUL API & Web App/1. Flask RestFUL API.srt 10.2 kB
  • 20. PyTorch Lightning/5. Training on Multiple GPU, Profiling and TPUs.srt 10.2 kB
  • 13. Building CNNs in TensorFlow with Keras/4. Constructing the CNN.srt 10.1 kB
  • 27. Object Detection/7. Single Shot Detectors (SSDs).srt 10.1 kB
  • 14. Assessing Model Performance/6. PyTorch Viewing Misclassifications.srt 10.1 kB
  • 11. Deep Learning in Computer Vision Introduction/16. Loss Functions.srt 10.1 kB
  • 28. Modern Object Detectors - YOLO, EfficientDet, Detectron2/6. Detectron2.srt 10.0 kB
  • 25. Siamese Network/4. Siamese Networks in PyTorch.srt 10.0 kB
  • 18. Building and Loading Advanced CNN Archiectures and Rank-N Accuracy/6. Getting the Rank-N Accuracy in Keras.srt 10.0 kB
  • 21. Transfer Learning and Fine Tuning/2. Transfer Learning in PyTorch Lightning.srt 9.9 kB
  • 10. OpenCV - Working With Video/7. Importing YouTube Videos into OpenCV.srt 9.8 kB
  • 11. Deep Learning in Computer Vision Introduction/15. Training a CNN.srt 9.8 kB
  • 20. PyTorch Lightning/2. Lightning Setup and Class.srt 9.8 kB
  • 3. OpenCV - Image Operations/2. Grayscaling Images.srt 9.6 kB
  • 1. Introduction/3. What Makes Computer Vision Hard.srt 9.6 kB
  • 39. Plant Doctor Detector YOLOv5/1. Plant Doctor Detector YOLOv5.srt 9.5 kB
  • 4. OpenCV - Image Segmentation/4. Counting Circles, Ellipses and Finding Waldo with Template Matching.srt 9.5 kB
  • 9. OpenCV Projects/2. GrabCut Algorithm for Background Removal.srt 9.4 kB
  • 45. BiT BigTransfer Classifier Keras/1. BiT BigTransfer Classifier Keras.srt 9.4 kB
  • 26. Face Recognition (Age, Gender, Emotion and Ethnicity) with Deep Learning/2. Facial Similarity Keras VGGFace.srt 9.4 kB
  • 3. OpenCV - Image Operations/8. Convolutions, Blurring and Sharpening Images.srt 9.3 kB
  • 4. OpenCV - Image Segmentation/3. Line, Circle and Blob Detection.srt 9.2 kB
  • 14. Assessing Model Performance/5. Keras - Confusion Matrix and Classification Report.srt 9.1 kB
  • 11. Deep Learning in Computer Vision Introduction/9. Pooling.srt 9.1 kB
  • 17. Advamced Convolutional Neural Networks/8. InceptionV3.srt 9.0 kB
  • 11. Deep Learning in Computer Vision Introduction/17. Backpropagation.srt 9.0 kB
  • 25. Siamese Network/1. Introduction to Siamese Networks.srt 8.9 kB
  • 9. OpenCV Projects/1. Tilt Shift Effects.srt 8.9 kB
  • 14. Assessing Model Performance/2. Assessing Model Performance.srt 8.9 kB
  • 28. Modern Object Detectors - YOLO, EfficientDet, Detectron2/1. Introduction to YOLO.srt 8.7 kB
  • 16. Visualizing What CNN's Learn/1. Visualizing CNN Filters or Feature Maps.srt 8.6 kB
  • 6. OpenCV - Image Analysis and Transformation/4. Filtering on Colour.srt 8.6 kB
  • 6. OpenCV - Image Analysis and Transformation/3. Comparing Images MSE and Structual Similarity.srt 8.6 kB
  • 51. Point Cloud Classification PointNet/1. Point Cloud Classification PointNet.srt 8.5 kB
  • 53. Medical Project - X-Ray Pneumonia Prediction/1. X-Ray Pneumonia Prediction.srt 8.4 kB
  • 6. OpenCV - Image Analysis and Transformation/5. Watershed Algorithm Marker-Dased Image Segmentation.srt 8.4 kB
  • 28. Modern Object Detectors - YOLO, EfficientDet, Detectron2/5. EfficientDet.srt 8.4 kB
  • 8. OpenCV - Facial Landmark Detection & Face Swaps/1. Facial Landmark Detection with Dlib.srt 8.4 kB
  • 11. Deep Learning in Computer Vision Introduction/13. Parameter Counts in CNNs.srt 8.4 kB
  • 8. OpenCV - Facial Landmark Detection & Face Swaps/2. Face Swapping with Dlib.srt 8.3 kB
  • 40. Deep Segmentation - U-Net, SegNet, DeeplabV3 and Mask R-CNN/3. PyTorch DeepLabV3.srt 8.2 kB
  • 26. Face Recognition (Age, Gender, Emotion and Ethnicity) with Deep Learning/4. Face Recognition PyTorch FaceNet.srt 8.1 kB
  • 17. Advamced Convolutional Neural Networks/10. EfficientNet.srt 8.1 kB
  • 47. Image Similarity using Metric Learning/1. Image Similarity using Metric Learning.srt 8.1 kB
  • 28. Modern Object Detectors - YOLO, EfficientDet, Detectron2/4. YOLO Evolution.srt 8.1 kB
  • 54. Medical Project - 3D CT Scan Classification/1. 3D CT Scan Classification.srt 8.1 kB
  • 49. Video Classification usign CNN+RNN/1. Video Classification usign CNN+RNN.srt 8.0 kB
  • 11. Deep Learning in Computer Vision Introduction/7. Stride.srt 8.0 kB
  • 11. Deep Learning in Computer Vision Introduction/1. Introduction to Convolution Neural Networks.srt 7.9 kB
  • 17. Advamced Convolutional Neural Networks/12. The ImageNet Dataset.srt 7.9 kB
  • 11. Deep Learning in Computer Vision Introduction/8. Activation Functions.srt 7.9 kB
  • 32. Pothole Detector - TinyYOLOv4/1. Pothole Detector - TinyYOLOv4.srt 7.9 kB
  • 57. OCR Captcha Cracker/1. OCR Captcha Cracker.srt 7.8 kB
  • 16. Visualizing What CNN's Learn/5. Class Maximization.srt 7.8 kB
  • 7. OpenCV - Motion and Object Tracking/3. Simple Object Tracking by Color.srt 7.8 kB
  • 13. Building CNNs in TensorFlow with Keras/3. Preprocessing Our Data.srt 7.8 kB
  • 22. Google DeepStream and Neural Style Transfer/6. Neural Style Transfer in PyTorch.srt 7.7 kB
  • 35. Drone Maritime Detector R-CNN/1. Drone Maritime Detector R-CNN.srt 7.7 kB
  • 44. Vision Transformers - ViTs/3. Vision Transformers in Keras.srt 7.7 kB
  • 9. OpenCV Projects/11. Detect Blur in Images.srt 7.7 kB
  • 43. Deep Fakes/1. Creating a Deep Fake.srt 7.7 kB
  • 44. Vision Transformers - ViTs/1. Introduction to Vision Transformers.srt 7.7 kB
  • 12. Building CNNs in PyTorch/9. Plot and Visualize Your Results.srt 7.6 kB
  • 22. Google DeepStream and Neural Style Transfer/1. Introduction to Google DeepDream Visualizations.srt 7.5 kB
  • 33. Mushroom Detector Detectron2/1. Mushroom Detector Detectron2.srt 7.5 kB
  • 40. Deep Segmentation - U-Net, SegNet, DeeplabV3 and Mask R-CNN/5. Detectron2 Mask R-CNN.srt 7.4 kB
  • 24. Generative Adversarial Networks (GANs)/2. How Do GANs Work.srt 7.4 kB
  • 10. OpenCV - Working With Video/6. Capturing Video using Screenshots.srt 7.3 kB
  • 17. Advamced Convolutional Neural Networks/5. ResNets.srt 7.2 kB
  • 17. Advamced Convolutional Neural Networks/4. VGG16 and VGG19.srt 7.2 kB
  • 36. Chess Piece YOLOv3/1. Chess Piece YOLOv3.srt 7.2 kB
  • 19. Using Callbacks in Keras and PyTorch/1. What are Callbacks.srt 7.2 kB
  • 12. Building CNNs in PyTorch/4. Data Loaders.srt 7.2 kB
  • 17. Advamced Convolutional Neural Networks/9. SqueezeNet.srt 7.0 kB
  • 40. Deep Segmentation - U-Net, SegNet, DeeplabV3 and Mask R-CNN/6. Train Mask R-CNN Shapes Dataset.srt 7.0 kB
  • 34. Website Region Detector YOLOv4 Darknet/1. Website Region Detector YOLOv4 Darknet.srt 6.9 kB
  • 10. OpenCV - Working With Video/2. Opening Video Files in OpenCV.srt 6.9 kB
  • 15. Improving Models and Advanced CNN Design/7. Batch Normalization.srt 6.9 kB
  • 11. Deep Learning in Computer Vision Introduction/4. 3D Convolutions and Color Images.srt 6.8 kB
  • 37. Bloodcell Detector YOLOv5/1. Bloodcell Detector YOLOv5.srt 6.8 kB
  • 16. Visualizing What CNN's Learn/4. Maximizing Filters.srt 6.8 kB
  • 17. Advamced Convolutional Neural Networks/6. Why ResNets Work So Well.srt 6.8 kB
  • 9. OpenCV Projects/7. SSDs in OpenCV.srt 6.8 kB
  • 14. Assessing Model Performance/7. PyTorch - Confusion Matrix and Misclassifications.srt 6.7 kB
  • 15. Improving Models and Advanced CNN Design/5. Data Augmentation.srt 6.7 kB
  • 24. Generative Adversarial Networks (GANs)/1. Introduction to GANs.srt 6.7 kB
  • 28. Modern Object Detectors - YOLO, EfficientDet, Detectron2/3. Training YOLO.srt 6.7 kB
  • 4. OpenCV - Image Segmentation/5. Finding Corners.srt 6.7 kB
  • 13. Building CNNs in TensorFlow with Keras/2. View and Inspect Data.srt 6.6 kB
  • 40. Deep Segmentation - U-Net, SegNet, DeeplabV3 and Mask R-CNN/4. Mask-RCNN Tensorflow Matterport.srt 6.6 kB
  • 50. Video Classification with Transformers/1. Video Classification with Transformers.srt 6.6 kB
  • 11. Deep Learning in Computer Vision Introduction/3. Feature Detectors.srt 6.6 kB
  • 10. OpenCV - Working With Video/4. Video Streams and CCTV - RTSP and IP.srt 6.6 kB
  • 28. Modern Object Detectors - YOLO, EfficientDet, Detectron2/2. How YOLO Works.srt 6.6 kB
  • 12. Building CNNs in PyTorch/2. Transformation Pipeline.srt 6.5 kB
  • 11. Deep Learning in Computer Vision Introduction/14. Why CNNs Work So Well On Images.srt 6.5 kB
  • 22. Google DeepStream and Neural Style Transfer/3. Google DeepDream in PyTorch.srt 6.5 kB
  • 13. Building CNNs in TensorFlow with Keras/5. Training the Model.srt 6.5 kB
  • 13. Building CNNs in TensorFlow with Keras/6. Plotting the Training Results.srt 6.3 kB
  • 56. Deploy your CV App using Flask RestFUL API & Web App/2. Flask Web App.srt 6.2 kB
  • 11. Deep Learning in Computer Vision Introduction/5. Kernel Size and Depth.srt 6.1 kB
  • 17. Advamced Convolutional Neural Networks/3. AlexNet.srt 6.1 kB
  • 9. OpenCV Projects/9. Inpainting to Restore Damaged Photos.srt 5.9 kB
  • 15. Improving Models and Advanced CNN Design/4. L1 and L2 Regularization.srt 5.9 kB
  • 42. Tracking with DeepSORT/2. DeepSORT with YOLOv5.srt 5.7 kB
  • 17. Advamced Convolutional Neural Networks/1. History and Evolution of Convolutional Neural Networks.srt 5.7 kB
  • 11. Deep Learning in Computer Vision Introduction/6. Padding.srt 5.7 kB
  • 24. Generative Adversarial Networks (GANs)/8. AnimeGAN.srt 5.5 kB
  • 38. Hard Hat Detector EfficentDet/1. Hard Hat Detector EfficentDet.srt 5.4 kB
  • 21. Transfer Learning and Fine Tuning/6. PyTorch Transfer Learning and Freezing Network Layers.srt 5.4 kB
  • 13. Building CNNs in TensorFlow with Keras/1. Loading Data.srt 5.3 kB
  • 15. Improving Models and Advanced CNN Design/6. Early Stopping.srt 5.2 kB
  • 25. Siamese Network/2. Training Siamese Networks.srt 4.9 kB
  • 15. Improving Models and Advanced CNN Design/3. Drop Out.srt 4.9 kB
  • 10. OpenCV - Working With Video/3. Saving or Recording Videos in OpenCV.srt 4.9 kB
  • 18. Building and Loading Advanced CNN Archiectures and Rank-N Accuracy/4. The Top-N or Rank-N Accuracy Metric.srt 4.7 kB
  • 41. Body Pose Estimation/1. Body Pose Estimation.srt 4.7 kB
  • 17. Advamced Convolutional Neural Networks/2. LeNet.srt 4.6 kB
  • 16. Visualizing What CNN's Learn/7. Grad-CAM Visualize What Influences Your Model.srt 4.6 kB
  • 10. OpenCV - Working With Video/5. Auto Reconnect to Video Streams.srt 4.5 kB
  • 27. Object Detection/5. Non Maximum Suppression.srt 4.5 kB
  • 27. Object Detection/3. Intersection Over Union.srt 4.4 kB
  • 2. Download Code and Setup Colab/2. Setup - Download Code and Configure Colab.srt 4.3 kB
  • 11. Deep Learning in Computer Vision Introduction/10. Fully Connected Layers.srt 4.3 kB
  • 11. Deep Learning in Computer Vision Introduction/11. Softmax.srt 4.0 kB
  • 24. Generative Adversarial Networks (GANs)/9. ArcaneGAN.srt 3.8 kB
  • 15. Improving Models and Advanced CNN Design/8. When Do We Use Regularization.srt 3.6 kB
  • 12. Building CNNs in PyTorch/6. Optimisers and Loss Function.srt 3.3 kB
  • 15. Improving Models and Advanced CNN Design/2. Introduction to Regularization.srt 2.9 kB
  • 2. Download Code and Setup Colab/1. Download Course Resources.html 804 Bytes
  • 0. Websites you may like/[FreeCourseSite.com].url 127 Bytes
  • 23. Autoencoders/0. Websites you may like/[FreeCourseSite.com].url 127 Bytes
  • 6. OpenCV - Image Analysis and Transformation/0. Websites you may like/[FreeCourseSite.com].url 127 Bytes
  • 0. Websites you may like/[CourseClub.Me].url 122 Bytes
  • 23. Autoencoders/0. Websites you may like/[CourseClub.Me].url 122 Bytes
  • 6. OpenCV - Image Analysis and Transformation/0. Websites you may like/[CourseClub.Me].url 122 Bytes
  • 0. Websites you may like/[GigaCourse.Com].url 49 Bytes
  • 23. Autoencoders/0. Websites you may like/[GigaCourse.Com].url 49 Bytes
  • 6. OpenCV - Image Analysis and Transformation/0. Websites you may like/[GigaCourse.Com].url 49 Bytes

随机展示

相关说明

本站不存储任何资源内容，只收集BT种子元数据(例如文件名和文件大小)和磁力链接(BT种子标识符)，并提供查询服务，是一个完全合法的搜索引擎系统。 网站不提供种子下载服务，用户可以通过第三方链接或磁力链接获取到相关的种子资源。本站也不对BT种子真实性及合法性负责，请用户注意甄别！
>