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djene-mengistu/README.md

Hi there, I'm Sime, Dejene Mengistu 👋

  • 🔭 I’m currently working on data- and annotation-efficient algorithms for industrial machine vision applications.
  • 🌱 Weakly-supervised and unsupervised algorithms for defect segmentation and anomaly detection.
  • 👯 I’m looking to collaborate on related topics of image segmentation in domains such as medical imaging and industrial machine vision.
  • 👯 I'm also interested in anomaly detection and machinery fault diagnosis.
  • 📫 How to reach me: djene.mengistu@gmail.com

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Languages and Tools:

python pandas pytorch scikit_learn seaborn tensorflow cplusplus git matlab opencv

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  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 9 2

  2. dseg_models dseg_models Public

    This repo contains implementation of deep learning-based steel surface defect segmentation models. Extensive experiments on several deep learning frameworks have been presented with various perform…

    Python 21 3

  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 14 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.

    10 1

  5. VIP_pytorch VIP_pytorch Public

    Forked from changzy00/pytorch-attention

    🦖Pytorch implementation of popular Attention Mechanisms, Vision Transformers, MLP-Like models and CNNs.🔥🔥🔥

    Python 1

  6. STAC STAC Public

    This work proposes STAC, a novel framework for weakly supervised defect localization that leverages saliency-guided transformer attention and pixel-level contrastive learning to achieve precise def…

    1