SimpleAICV:pytorch training and testing examples.

This project leverages deep learning to classify plant diseases from images, using a custom ResNet-9 architecture implemented in PyTorch. By enabling early detection of plant diseases, it aims to reduce crop losses and promote sustainable agriculture, showcasing the potential of AI in addressing global food security challenges.

基于ResNet的手写数字识别

The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more

Developed end-to-end app to generate cartoons image description

🤘 TT-NN operator library, and TT-Metalium low level kernel programming model.

This is a multi-task neural network that utilizes the GELAN backbone and ViT encoder to perform multiple tasks, maximizing multi-class classification performance.

This project is based on ResNet101 and YOLOv8 to detect the focus that cause high myopia

A summative coursework for CSC8635 Machine Learning with Project

Assignment submission for CV703 course (Visual Recognition and Object Detection) @ MBZUAI

Code for the Nature Scientific Reports paper "Pathologist-level classification of histologic patterns on resected lung adenocarcinoma slides with deep neural networks." A sliding window framework for classification of high resolution whole-slide images, often microscopy or histopathology images.

Final project for 6.8301 - Computer Vision (spring 2024)

A toolbox of vision models and algorithms based on MindSpore

VGAResNet: A Unified Visibility Graph Adjacency Matrix-Based Residual Network for Chronic Obstructive Pulmonary Disease Detection Using Lung Sounds

Implementation of popular deep learning networks with TensorRT network definition API

Minerva project includes the minerva package that aids in the fitting and testing of neural network models. Includes pre and post-processing of land cover data. Designed for use with torchgeo datasets.

Using ResNet, accurately detect tea plant diseases, improving agricultural management and enhancing plant health with advanced technology.

A lightweight and extensible toolbox for image classification

带你从零实现一个高性能的深度学习推理库，支持大模型 llama2 、Unet、Yolov5、Resnet等模型的推理。Implement a high-performance deep learning inference library step by step

[WACV 2024 Oral] - ARNIQA: Learning Distortion Manifold for Image Quality Assessment