Implementation of science project for my master's degree. Scripts for segmentation task: UNET, SEGNET, FCN-8, K-Mean

This repository implements and evaluates SegNet, U-Net, and models from segmentation_models.pytorch for vehicle segmentation using PyTorch. It showcases these models' capabilities in accurately segmenting vehicles in complex scenes, demonstrating cutting-edge deep learning techniques in computer vision

A repo for Segnet training from start to finish in two different ways

This project implements semantic image segmentation using two popular convolutional neural network architectures: U-Net and SegNet. Semantic image segmentation involves partitioning an image into multiple segments, each representing a different class.

Algorithm which can detect lanes in a road and calculate and display features like offset from the center of the lane, radius of curvature of the road etc.

Image segmentation implemented using pytorch on a COCO format Dataset of Ingredients with various models including U-NET, U-NET++, SegNet and DeepLabV3+

Enhancing lane detection systems using deep learning models: U-Net and SegNet for the course ECE-5554 Computer Vision

PyTorch implementation for Semantic Segmentation, include FCN, U-Net, SegNet, GCN, PSPNet, Deeplabv3, Deeplabv3+, Mask R-CNN, DUC, GoogleNet, and more dataset

AI solution for detecting individuals crossing the safety line on the subway platform

The official implementation of "Encoder-Decoder Based Convolutional Neural Networks with Multi-Scale-Aware Modules for Crowd Counting"

Performance of various image segmentation models.

A comparative study for skin lesion segmentation and melanoma detection where deep learning methods can perform very well without complex pre-processing techniques except for normalization and augmentation.

Coding Neural Network architectures using PyTorch

CNN architectures for multiclass semantic segmentation of esophageal diseases

Проект по сегментации кожных новообразований с использованием архитектур сегментационных сетей.

PyTorch implementation of U-Net and SegNet segmentation models for detecting melanoma, along with pre-trained models and utility functions for evaluation.

Image Segmentation Paper Review and Implementation