Traditional Machine learning and Deep learning approaches to classify Search for extraterrestrial intelligence Signal

Swin Transformer implementations for TensorFlow/Keras

[Ecological Informatics] TensorFlow implementation for the paper "Bag of tricks for long-tail visual recognition of animal species in camera-trap images"

Code for automated brain tumor segmentation from MRI scans using CNNs with attention mechanisms, deep supervision, and Swin-Transformers. Based on my Master's dissertation project at Brunel University, it features 3 deep learning models, showcasing integration of advanced techniques in medical image analysis.

building AVA from ex-machina; a lightweight multi-modal system from scratch, just for learning & experimentation

Kaggle Competition Bronze Medal 🥉 (205th out of 3537 teams)

This repository contains an image classification model for the subject AI Convergence and Application held on Handong Global University (HGU)

This repo hosts the water body extraction from satellite images using Trans Deeplab model.

Real-time ReID Tracking w/. Lite but Strong Feature Extractor & GAN

Swin Transformers, short for "Shifted Windows," were introduced in the paper titled "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" by Liu et a. (2021). Unlike traditional transformers, Swin Transformers divide the image into non-overlapping shifted windows, enabling efficient and scalable computation.

swin transformer pytorch starter

Comprehensive Performance Analysis of Three Pretrained Transformer Models (ViT, Swin, and MaxViT) on ImageNet and Fine-tuned on the NIH Chest X-rays Dataset for Classifying 14 Chest Radiograph Pathologies

This is a warehouse for Agent-Attention-Models based on pytorch framework, can be used to train your image datasets.

This is the key code of the paper "CCST: Crowd Counting with Swin Transformer"

This project compares the performance of Swin-Transformer v2 implemented in JAX and PyTorch.

Official Repository for the paper "Feature Extraction for Generative Medical Imaging Evaluation: New Evidence Against an Evolving Trend".

This is a warehouse for STL-Pytorch-model, can be used to train your image-datasets for vision tasks.

TensorFlow implementation of EGIC (to be announced)

Vision Transformer

CascadeRCNN implementation using PyTorch