Autonomous Vehicle System Design - Transformers for Computer Vision Applications

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Transformers for Computer Vision Applications

1.Introduction

Introduction to the Course

2.Overview of Transformer Networks

Introduction to Transformers The Rise of Transformers Inductive Bias in DNNs Attention: General Deep Learning Idea Attention in NLP Is Attention All We Need?Quiz: Attention and Inductive Bias Self-Attention Mechanism Self-Attention Matrix Equations Multihead Attention Encoder-Decoder Attention Transformers Pros and Cons Unsupervised and Self-Supervised Pretraining Quiz: Transformers and Multihead Attention

Mini Project

Neural Machine Translation with a Transformer and Keras

3.Transformers in Computer Vision

Introduction to Transformers in Computer Vision Encoder-Decoder Design Pattern Convolutional Encoders Self-Attention vs. Convolution Quiz: Encoder-Decoder Architecture and Attention Mechanism in Computer Vision Spatial vs. Channel vs. Temporal Attention Local vs. Global Attention Pros and Cons of Attention in CV Quiz: Attention in Computer Vision

Project

Vision Transformer for Image Classification

4.Transformers in Image Classification

Image Classification with Vision Transformer (ViT and DeiT)Shifter Window (Swin) Transformers Quiz: Transformers in Image Classification

Mini Project

Fine-Tuning Vision Transformers for Image Classification

5.Transformers in Object Detection

Object Detection Methods Review DEtection TRansformers (DETR)Quiz: Transformers in Object Detection

6.Transformers in Semantic Segmentation

Image Segmentation Using ConvNets Image Segmentation Using Transformers Quiz: Transformers in Semantic Segmentation

7.Spatio-Temporal Transformers

Spatio-Temporal Transformers Quiz: Spatio-Temporal Transformers

Mini Project

Object Detection with Vision Transformers

8.Wrap Up

Mock Interview

Autonomous Vehicle System Design