Introduction to Dl4cv Wis Spring 2021 Tutorial 7 Sequences
Let's dive into the details surrounding Dl4cv Wis Spring 2021 Tutorial 7 Sequences. RNNs, LSTM, Tranformeres in Computer Vision Lecturer: Akhiad Bercovich.
Dl4cv Wis Spring 2021 Tutorial 7 Sequences Comprehensive Overview
Recurrent Neural Networks (RNNs), Deep Features, Image Embedding, Saliency via Occlusion, Class Activation Maps (CAM), Grad-CAM, Feature Inversion, Neural ... SGD, Learning Rate Decay, Adam, Dropout, BatchNorm, Augmentations Lecturer: Shai Bagon.
Vectorization, Broadcasting, Tensor Multiplication, Gather, Fold/Unfold, Dataloaders Lecturer: Ben Feinstein.
Summary & Highlights for Dl4cv Wis Spring 2021 Tutorial 7 Sequences
- Tensor operations, MLP implementation, Backpropagation, Optimizers Lecturer: Shir Amir.
- CNNs, Padding, Conv2D, Receptive Field, Transposed Convolution, Max Pooling Lecturer: Assaf Shocher.
- Introduction , Course logistics, Basic Supervised Learning setup, Linear regression, Normal equations, Gradient descent, Feature ...
- AlexNet, VGG, ResNet, EfficientNet Lecturer: Dror Moran.
- Localization, Object Detection, RPN, Semantic Segmentation, FCN, Mask-RCNN Lecturer: Shai Bagon.
That wraps up our extensive overview of Dl4cv Wis Spring 2021 Tutorial 7 Sequences.