Molemi App is a AI (Deep Learning) based plant disease recognition application that can identify up to 10 various types of plant diseases by analyzing plant leaves.

Rice Disease Detection application to detect diseases that often attack rice crops including Brown Spot, Hispa, and Leaf Blast).

Android app for plant disease identification using ML

AI powered plant disease detection and assistance platform currently available as an App and API.

Plant Disease Detection using ML model and Android App

Accounting to almost 6.0% of the total tomato production in the world. Tomato is the third most significant vegetable of India by sharing 8.5% of all out vegetable creation.This shows The importanc…

Smart India Hackathon 2k18 project for detecting plant disease based on images of plant leaves having disease

[ICCV2023] This is an official implementation for "Scale-Aware Modulation Meet Transformer".

Plant Diseases Classification using AlexNET

Escaping the Big Data Paradigm with Compact Transformers, 2021 (Train your Vision Transformers in 30 mins on CIFAR-10 with a single GPU!)

A Deepfake detector based on hybrid EfficientNet CNN and Vision Transformer archietcture. The model is explainable by rendering a heatmap visualization of the Transformer Relevancy / Attention map.

Official PyTorch Code for Hybrid Window Attention Based Transformer Architecture for Brain Tumor Segmentation: Solution for FeTS 2022 Task 2

[MICCAI 2022] Official Implementation for "Hybrid Spatio-Temporal Transformer Network for Predicting Ischemic Stroke Lesion Outcomes from 4D CT Perfusion Imaging"

[ICANN 2022 Oral] This repository includes the official project of TFCNs, presented in our paper: TFCNs: A CNN-Transformer Hybrid Network for Medical Image Segmentation

HyFormer: Hybrid Transformer and CNN For Pixel-level Multispectral Image Classification

Hybrid structure of Vision Transformer and ResNet50x3

Official Implementation of ResViT: Residual Vision Transformers for Multi-modal Medical Image Synthesis

"SwinDepth: Unsupervised Depth Estimation using Monocular Sequences via Swin Transformer and Densely Cascaded Network" (ICRA 2023)

A PyTorch implementation of CMT based on paper CMT: Convolutional Neural Networks Meet Vision Transformers.

PyTorch Implementation of CvT: Introducing Convolutions to Vision Transformers

[CADL'22, ECCVW] Official repository of paper titled "EdgeNeXt: Efficiently Amalgamated CNN-Transformer Architecture for Mobile Vision Applications".

Source code for BiRSwinT: Bilinear Full-Scale Residual Swin-Transformer for Fine-Grained Driver Behavior Recognition

reimplemention of cycleGAN and improve it lightly

A PyTorch implementation of VITGAN: Training GANs with Vision Transformers

This is a re-implementation of TransGAN: Two Pure Transformers Can Make One Strong GAN (NeurIPS 2021) in PyTorch.

A PyTorch implementation of ViTGAN based on paper ViTGAN: Training GANs with Vision Transformers.

Core code for " Transformer-based Generative Adversarial Network for Brain Tumor Segmentation"

This repository uses modules from Swin Transformer to build Transformer-based Generative Adversarial Networks (GANs) models.

Vision Transformer and Convolutional Neural Network Cycle-Consistent Generative Adversarial