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    Models/Object Detection/Nihil-Drf/FathomNet-2026-4thplace-Model
    Object Detectionultralyticsmit

    FathomNet-2026-4thplace-Model

    by Nihil-Drf

    Identifier
    Model ID
    Nihil-Drf/FathomNet-2026-4thplace-Model

    Tags

    ultralyticsobject-detectioncomputer-visiondeep-learningpytorchyolomarine-biologyfathomnetcvprpositive-unlabeled-learningcompetition-solutiondataset:FathomNet/fathomnet2026arxiv:2508.10104license:mitregion:us

    Use FathomNet-2026-4thplace-Model on Mixpeek

    Build multimodal processing pipelines with this model and others. Extract features, run inference, and set up retrieval in Mixpeek Studio.

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    How It Runs on Mixpeek

    On Mixpeek, FathomNet-2026-4thplace-Model runs as a managed extractor inside a processing pipeline. Point a bucket of object detection data at it, and Mixpeek handles GPU provisioning, batching, retries, and writing the outputs into a vector store you can query.

    Extractor outputs land in the Mixpeek Vector Store (MVS), where you can combine them with retrieval, reranking, and filter stages to build end-to-end search and agent-perception pipelines, no model-serving infrastructure to maintain.