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Name: djene_mengistu

Type: User

Company: Xidian University

Bio: Postdoctoral researcher Machine vision and deep learning

Location: Xi'an, Shaanxi, China

Hi there, I'm Sime, Dejene Mengistu 👋

🔭 I’m currently working on data-efficient deep learning-based algorithms for industrial machine vision applications.
🌱 I’m currently studying weakly-supervised and unsupervised algorithms for defect segmentation and anomaly detection.
👯 I’m looking to collaborate on unsupervised segmentation methods using multi-modal datasets of image, text and audio for general purpose method.
👯 I'm also interested in medical image analysis, anomaly detection and machinery fault diagnosis.
📫 How to reach me: [email protected]

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djene_mengistu's Projects

unimatch

[CVPR 2023] Revisiting Weak-to-Strong Consistency in Semi-Supervised Semantic Segmentation

unsupervised-anomaly-detection-with-ssim-ae

visual_prompting

Official implementation and data release of the paper "Visual Prompting via Image Inpainting".

vit-pytorch

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

wseg-pixel-to-prototype

[CVPR'22] Weakly Supervised Semantic Segmentation by Pixel-to-Prototype Contrast

wsl4ids

Scribbles or Points-based weakly-supervised learning for medical image segmentation, a strong baseline, and tutorial for research and application.

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