gram-ai/capsule-networks
A PyTorch implementation of the NIPS 2017 paper "Dynamic Routing Between Capsules".
This project offers a PyTorch implementation of Capsule Networks, a neural network architecture particularly effective for image recognition. It takes an image as input and outputs a classification of the objects or parts within it, even when they overlap. This would be used by a machine learning engineer or researcher experimenting with advanced image classification models beyond standard convolutional neural networks.
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Use this if you are a machine learning researcher or engineer interested in exploring Capsule Networks for robust image recognition, especially for scenarios involving overlapping objects, and prefer working with PyTorch.
Not ideal if you are a beginner looking for a simple, off-the-shelf image classification solution, as this requires some understanding of deep learning frameworks and model training.
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Nov 09, 2018
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