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djene-mengistu/README.md

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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Languages and Tools:

python pandas pytorch scikit_learn seaborn tensorflow cplusplus git matlab opencv

Pinned

  1. simEps simEps Public

    This repo contains implementation of semi-supervised defect segmentation based on pairwise similarity map consistency and ensemble-based cross pseudo labels

    Python 5 2

  2. dseg_models dseg_models Public

    This repo contains implementation of deep learning-based steel surface defect segmentation models.

    Python 9 2

  3. UAPS UAPS Public

    This repo contains implementation of uncertainty estimation, rectification, and minimization for guiding the pseudo-label learning in semi-supervised defect segmentation setting.

    Python 8 1

  4. Machine-Vision-and-Anomaly-Detection-Papers Machine-Vision-and-Anomaly-Detection-Papers Public

    This repo contains state-of-the-art deep learning models for industrial anomaly detection, defect segmentation, detection, and classification, with other industrial machine vision applications.

    3 1

  5. Awesome-Segment-Anything Awesome-Segment-Anything Public

    Forked from liliu-avril/Awesome-Segment-Anything

    This repository is for the first comprehensive survey on Meta AI's Segment Anything Model (SAM).

    1

  6. AnomalyGPT AnomalyGPT Public

    Forked from CASIA-IVA-Lab/AnomalyGPT

    The first LVLM based IAD method!

    Python 1