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Open-source Tri-Net v2 released for unified monkeypox detection

By PulseAugur Editorial · [1 sources] ·

Researchers have released Tri-Net v2, an open-source implementation of their Scientific Reports paper focused on monkeypox detection. This framework includes a leakage-free data preparation pipeline, support for multiple CNN backbones, ensemble strategies, and Grad-CAM explainability. The project aims to facilitate reproduction, validation, and extension of their work, with the paper already garnering significant attention. AI

IMPACT Provides a reproducible framework for monkeypox detection research, potentially accelerating advancements in medical AI.

RANK_REASON The cluster describes the release of an open-source implementation of a scientific paper, which falls under research. [lever_c_demoted from research: ic=1 ai=1.0]

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AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Open-source Tri-Net v2 released for unified monkeypox detection

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The cluster describes the release of an open-source implementation of a scientific paper, which falls under research. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. r/MachineLearning TIER_1 English(EN) · /u/Rich-Fruit-326 ·

    Tri-Net v2: Open-source implementation of our Scientific Reports paper on unified skin lesion and symptom-based monkeypox detection [R]

    <table> <tr><td> <a href="https://www.reddit.com/r/MachineLearning/comments/1v26adz/trinet_v2_opensource_implementation_of_our/"> <img alt="Tri-Net v2: Open-source implementation of our Scientific Reports paper on unified skin lesion and symptom-based monkeypox detection [R]" src…

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