Polyp segmentation on the Kvasir-SEG dataset using deep learning models like UNet, UNet++, PSPNet, and DeepLabV3Plus with ResNet50 and MobileNetV2 encoders.

This project aims to classify different types of fruits using deep learning. The objective is to build a model that can accurately identify the type of fruit based on images.

This repository contains a Python application for emotion recognition using facial expressions. The application utilizes computer vision techniques and deep learning models to analyze facial expressions , aiming to detect and classify emotions based on input images or video streams.

This is an official pytorch implementation of WideHRNet: an Efficient Model for Human Pose Estimation Using Wide Channels in Lightweight High-Resolution Network.