Showing 3 open source projects for "matlab image classification"

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  • 1
    ClassyVision

    ClassyVision

    An end-to-end PyTorch framework for image and video classification

    Classy Vision is a PyTorch-based framework designed for large-scale training and deployment of state-of-the-art image and video classification models. Developed by Facebook Research, it serves as an end-to-end system that simplifies the process of training at scale, reducing redundancy and friction in moving from research to production. Unlike traditional computer vision libraries that focus solely on modular components, Classy Vision provides a complete and unified framework, featuring distributed training, reproducible experiments, and flexible configuration tools. ...
    Downloads: 0 This Week
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  • 2
    Gluon CV Toolkit

    Gluon CV Toolkit

    Gluon CV Toolkit

    ...It features training scripts that reproduce SOTA results reported in latest papers, a large set of pre-trained models, carefully designed APIs and easy-to-understand implementations and community support. From fundamental image classification, object detection, semantic segmentation and pose estimation, to instance segmentation and video action recognition. The model zoo is the one-stop shopping center for many models you are expecting. GluonCV embraces a flexible development pattern while is super easy to optimize and deploy without retaining a heavyweight deep learning framework.
    Downloads: 0 This Week
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  • 3
    RefineNet

    RefineNet

    RefineNet: Multi-Path Refinement Networks

    RefineNet is a MATLAB-based framework for semantic image segmentation and general dense prediction tasks. It implements the architecture presented in the CVPR 2017 paper RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation and its extended version published in TPAMI 2019. The framework uses multi-path refinement and improved residual pooling to achieve high-quality segmentation results across multiple benchmark datasets.
    Downloads: 2 This Week
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