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Search: pytorch-image-models
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Showing 10 results from 250
piyushpathak03/Recommendation-systems
GitHub Jupyter Notebook GNU General Public License v3.0Recommendation Systems This is a workshop on using Machine Learning and Deep Learning Techniques to build Recommendation Systesm Theory: ML & DL Formulation, Prediction vs. Ranking, Similiarity, Biased vs. Unbiased Paradigms: Content-based, Collaborative filtering, Knowledge-based, Hybrid and En... Read more
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eugenesiow/super-image
GitHub Python Apache License 2.0Image super resolution models for PyTorch.
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xmuyzz/3D-CNN-PyTorch
GitHub PythonPyTorch implementation for 3D CNN models for medical image data (1 channel gray scale images).
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vincentfpgarcia/from-pytorch-to-coreml
GitHub Python MIT LicenseA simple guide that explains the steps from training a simple PyTorch image classifier to converting the generated neural network into a CoreML model ready for production
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himanshub1007/Alzhimers-Disease-Prediction-Using-Deep-learning
GitHub Python# AD-Prediction Convolutional Neural Networks for Alzheimer's Disease Prediction Using Brain MRI Image ## Abstract Alzheimers disease (AD) is characterized by severe memory loss and cognitive impairment. It associates with significant brain structure changes, which can be measured by magnetic r... Read more
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yusukeurakami/dreamer-pytorch
GitHub Python MIT Licensepytorch-implementation of Dreamer (Model-based Image RL Algorithm)
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sithu31296/sota-backbones
GitHub Python MIT LicenseA collection of SOTA Image Classification Models in PyTorch
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sayakpaul/cmmd-pytorch
GitHub Python Apache License 2.0PyTorch implementation of CLIP Maximum Mean Discrepancy (CMMD) for evaluating image generation models.
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YBYBZhang/VideoElevator
GitHub Python[AAAI 2025] Official pytorch implementation of "VideoElevator: Elevating Video Generation Quality with Versatile Text-to-Image Diffusion Models"
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AnkurDeria/HSI-Traditional-to-Deep-Models
GitHub Jupyter NotebookPytorch and Keras Implementations of Hyperspectral Image Classification -- Traditional to Deep Models: A Survey for Future Prospects.
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