73 - Image Segmentation using U-Net - Part1 (What is U-net?)
Many deep learning architectures have been proposed to solve various image processing challenges. SOme of the well known architectures include LeNet, ALexNet, VGG, and Inception. U-net is a relatively new architecture proposed by Ronneberger et al. for semantic image segmentation. This video explains the U-Net architecture; a good understanding is essential before coding.
Link to the original U-Net paper: https://arxiv.org/abs/1505.04597
The code from this video is available at: https://github.com/bnsreenu/python_for_microscopists
Видео 73 - Image Segmentation using U-Net - Part1 (What is U-net?) канала DigitalSreeni
Link to the original U-Net paper: https://arxiv.org/abs/1505.04597
The code from this video is available at: https://github.com/bnsreenu/python_for_microscopists
Видео 73 - Image Segmentation using U-Net - Part1 (What is U-net?) канала DigitalSreeni
Показать
Комментарии отсутствуют
Информация о видео
Другие видео канала
74 - Image Segmentation using U-Net - Part 2 (Defining U-Net in Python using Keras)Convolutional Neural Networks (CNNs) explainedBut what is a Neural Network? | Deep learning, chapter 1180 - LSTM Autoencoder for anomaly detectionLecture 11 | Detection and SegmentationWhen deep learning meets satellite imageryConvolution Neural Networks - EXPLAINEDImplementing original U-Net from scratch using PyTorch177 - Semantic segmentation made easy (using segmentation models library)Mask Region based Convolution Neural Networks - EXPLAINED!75 - Image Segmentation using U-Net - Part 3 (What are trainable parameters?)Bioimage Analysis 3: Segmentation (Anne Carpenter)Convolutional Neural Networks | MIT 6.S191CV3DST - Semantic Segmentation185 - Hyperparameter tuning using GridSearchCV77 - Image Segmentation using U-Net - Part 5 (Understanding the data)Image Segmentation Loss: IoU vs Dice Coefficient76 - Image Segmentation using U-Net - Part 4 (Model fitting, checkpoints, and callbacks)Convolutional Neural Network (CNN) | Convolutional Neural Networks With TensorFlow | Edureka