Semantic segmentation model with the fusion of deeplabv3plus, hed and attention loss
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Updated
Aug 30, 2019 - Python
Semantic segmentation model with the fusion of deeplabv3plus, hed and attention loss
Some notes from various research papers
An approach for pixel-based classification of drivable parts of the road (known as Semantic Segmentation). Project 12 of Udacity's Self-Driving Car Engineer Nanodegree Program.
TensorFlow-based semantic segmentation codes.
This repository containis code for semantic segmentation of satellite image using U-Net architecture.
Real time semantic slam in ROS with a hand held RGB-D camera
Semantic segmentation of Nucleus to advance medical discovery using U-Net++.
Hybrid Feature Extraction for Chest xray
Diabetic retinpopath classfiction using trnasfer learning and Data augmentation
Analysis of the possibility of movement measurement on video recordings of the ICSI procedure using machine learning methods.
Self-Supervised Semantic Segmentation with Object Detection and Depth Estimation
Lightweight Neural Network for Semantic Segmentation using Knowledge Distillation (Accepted by AICAS 2022)
HISDF (Human Instance, Skeleton, and Depth Fusion) is a unified model that fuses human instance segmentation, skeletal structure estimation, and depth prediction to achieve holistic human perception from visual input.
Minimalistic Image Labelling Framework (MILF): A simple utility for pixel-wise image annotations.
Segmenting the functional tissue units of colon histopathology images.
Multi-Class Semantic Segmentation on India's Satellite Images.This project addresses the broader issue of semantic segmentation of satellite images by aiming at classifying each pixel as belonging to a Building & Road or not. We developed a Convolutional Neural Network suitable for this task, inspired from the U-net [7]. We trained our model on …
Tree Species Segmentation in High-Resolution Aerial Imagery
Multi-Task Learning
Federated Learning for semantic segmentation using Openfl and Pytorch
HistoSeg++: Delving deeper with attention and multiscale feature fusion for biomarker segmentation. Accepted in 12th International Conference on Biomedical and Bioinformatics Engineering (ICBBE 2025)
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