AMLResearchProject/all-classifiers-2019
A collection of computer vision projects for Acute Lymphoblastic Leukemia classification/early detection.
Implements multiple deep learning architectures (Caffe, Keras/TensorFlow, FastAI ResNets, Intel Movidius NCS) trained on augmented microscopy datasets to enable comparative performance analysis across frameworks. Includes data augmentation pipelines to expand training datasets, custom CNN architectures (AllCNN), and edge-device optimization via neural compute stick deployment for resource-constrained environments.
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MIT
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Jul 22, 2020
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