This project implements federated learning using a ResNet-34 model to classify chest X-ray images into various medical conditions. By distributing the training process across multiple clients holding local datasets, the approach ensures data privacy and leverages the power of decentralized learning.

Implementing UNet and ResNet34_UNet from scratch with Pytorch for Oxford-IIIT Pet Dataset Binary Semantic Segmentation

A CLI tool that utilizes a ResNet convolutional neural network to recognize content in images and sort them into classes.

Employing a fusion of UNet and ResNet architectures, the project endeavors to achieve multiclass semantic segmentation of sandstone images. Through deep learning techniques, it seeks to uncover microstructural features across various geological classifications.

Audio classification model. PyTorch.

Create ResNet

Multi-label defect detection for Solar Cells from Electroluminescence images of the modules, using Deep Learning

Capstone Project - brainstation

A streamlined image classifier using to accurately identify distinct sports ball.

Sorry, This repository has become a tmp. See <MyResNet> Repo. [Jan 19 2024]

Plant Disease Classification using ResNet

This repository contains a PyTorch implementation for classifying the Oxford IIIT Pet Dataset using KNN and ResNet. The goal is to differentiate the results obtained using these two approaches.

Classify alcohols and its snacks

Applying Deep Learning Techniques to determine fish feeding Status

Tensorflow 2 implementations of ResNet-18, ResNet-34, ResNet-50, ResNet-101, and ResNet-152 from Deep Residual Learning for Image Recognition by Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun (2015)

This project compares two learning paradigm, namely transfer-learning and self-supervised learning in a classification task of three retina disorders CNV, DME and DUSEN in addition to the normal condition using an OCT B-scans

Residual Connections in CNNs for cifar 10

This repository contains the code and results for a CIFAR10 image classification project using a custom ResNet34 model.

Handwritten Bangla Character Classification using ResNet-34 trained using BanglaLekha Dataset. System has been implemented in PyTorch. For details, see the README file.