Name: djene_mengistu
Type: User
Company: Xidian University
Bio: Postdoctoral researcher
Machine vision and deep learning
Location: Xi'an, Shaanxi, China
djene_mengistu's Projects
[CVPR 2022] Learning Affinity from Attention: End-to-End Weakly-Supervised Semantic Segmentation with Transformers
12 Weeks, 24 Lessons, AI for All!
[CVPR 2024] Alpha-CLIP: A CLIP Model Focusing on Wherever You Want
An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.
The first LVLM based IAD method!
š Papers & tech blogs by companies sharing their work on data science & machine learning in production.
Awesome List of Attention Modules and Plug&Play Modules in Computer Vision
Awesome things about domain generalization, including papers, code, etc.
A collection of research materials on explainable AI/ML
Awesome Incremental Learning
Paper list and datasets for industrial image anomaly detection.
A selection of state-of-the-art research materials on trajectory prediction
A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.
A collection of resources and papers on Diffusion Models
This repository is for the first comprehensive survey on Meta AI's Segment Anything Model (SAM).
A curated list of facial expression recognition in both 7-emotion classification and affect estimation.
A comprehensive list of weakly supervised semantic segmentation (WSSS) works from 2014 to 2022.
Recent weakly supervised semantic segmentation paper
This repository contains the code of the CVPR 2022 paper "Image Segmentation Using Text and Image Prompts".
official code for paper entitled "Component-aware anomaly detection framework for adjustable and logical industrial visual inspection"
Official repository of "Diffusion Adversarial Representation Learning for Self-supervised Vessel Segmentation", ICLR 2023.
Understanding Deep Learning - Simon J.D. Prince
This repository contains implementation of ResNet for surface defect classification, with detailed analysis of results.
Source codes for the paper "Deep Learning Algorithms for Rotating Machinery Intelligent Diagnosis: An Open Source Benchmark Study"
React
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