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    vJEPA-2

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    PyTorch code and models for VJEPA2 self-supervised learning from video

    ...Trained representations transfer well to downstream tasks such as action recognition, temporal localization, and video retrieval, often with simple linear probes or light fine-tuning. The repository typically includes end-to-end recipes—data pipelines, augmentation policies, training scripts, and evaluation harnesses.
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    Surface Defect Detection Dataset Papers

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    Constantly summarizing open source dataset and critical papers

    At present, surface defect equipment based on machine vision has widely replaced artificial visual inspection in various industrial fields, including 3C, automobiles, home appliances, machinery manufacturing, semiconductors and electronics, chemical, pharmaceutical, aerospace, light industry and other industries. Traditional surface defect detection methods based on machine vision often use conventional image processing algorithms or artificially designed features plus classifiers. Generally speaking, imaging schemes are usually designed by using the different properties of the inspected surface or defects. ...
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    Learn_Deep_Learning_in_6_Weeks

    Learn_Deep_Learning_in_6_Weeks

    This is the Curriculum for "Learn Deep Learning in 6 Weeks"

    Learn_Deep_Learning_in_6_Weeks compresses an introductory deep learning curriculum into six weeks of structured learning and practice. It begins with neural network fundamentals and moves through convolutional and recurrent architectures, optimization strategies, regularization, and transfer learning. The materials emphasize code-first understanding: building small models, training them on accessible datasets, and analyzing their behavior. Each week culminates in a tangible outcome—such as a...
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