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A Survey on Transformer in CV.
This repository accompanies our paper Unlocking the Heart Using Adaptive Locked Agnostic Networks and enables replication of the key results.
HydraViT is a PyTorch implementation of the HydraViT model, an adaptive multi-branch transformer for multi-label disease classification from chest X-ray images. The repository provides the necessary code to train and evaluate the HydraViT model on the NIH Chest X-ray dataset.
An easy and minimal implementation of the Visual Transformer (ViT) in PyTorch, from scratch!
The repository contains supplementary material to my Master's thesis - Fine-grained Visual Recognition with Side Information
Using Visual Transformers to train a basic image classification model to classify images of lions, tigers, cheetahs, tigers and leopards
Comparison of various deep learning-based medical imaging methods for diagnosing and classifying Alzheimer’s disease at different stages.
Methodology used to classify face images based on unknown criteria as part of a datachallenge organised at Telecom Paris
Simple implementation of CBIR with a pretrained ViT model and local Deeplake DB
🤖 Segmentação de faixas de estrada utilizando o Segformer