Showing 4 open source projects for "hyperspectral image dataset"

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  • 1
    CO3D (Common Objects in 3D)

    CO3D (Common Objects in 3D)

    Tooling for the Common Objects In 3D dataset

    CO3Dv2 (Common Objects in 3D, version 2) is a large-scale 3D computer vision dataset and toolkit from Facebook Research designed for training and evaluating category-level 3D reconstruction methods using real-world data. It builds upon the original CO3Dv1 dataset, expanding both scale and quality—featuring 2× more sequences and 4× more frames, with improved image fidelity, more accurate segmentation masks, and enhanced annotations for object-centric 3D reconstruction. ...
    Downloads: 0 This Week
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  • 2
    fastMRI

    fastMRI

    A large open dataset + tools to speed up MRI scans using ML

    fastMRI is a large-scale collaborative research project by Facebook AI Research (FAIR) and NYU Langone Health that explores how deep learning can accelerate magnetic resonance imaging (MRI) acquisition without compromising image quality. By enabling reconstruction of high-fidelity MR images from significantly fewer measurements, fastMRI aims to make MRI scanning faster, cheaper, and more accessible in clinical settings. The repository provides an open-source PyTorch framework with data...
    Downloads: 0 This Week
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  • 3
    ImageAI

    ImageAI

    A python library built to empower developers

    ImageAI is an easy-to-use Computer Vision Python library that empowers developers to easily integrate state-of-the-art Artificial Intelligence features into their new and existing applications and systems. It is used by thousands of developers, students, researchers, tutors and experts in corporate organizations around the world. You will find features supported, links to official documentation as well as articles on ImageAI. ImageAI is widely used around the world by professionals,...
    Downloads: 35 This Week
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  • 4
    Tensor2Tensor

    Tensor2Tensor

    Library of deep learning models and datasets

    Deep Learning (DL) has enabled the rapid advancement of many useful technologies, such as machine translation, speech recognition and object detection. In the research community, one can find code open-sourced by the authors to help in replicating their results and further advancing deep learning. However, most of these DL systems use unique setups that require significant engineering effort and may only work for a specific problem or architecture, making it hard to run new experiments and...
    Downloads: 1 This Week
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