Rishit-dagli/GLOM-TensorFlow
An attempt at the implementation of GLOM, Geoffrey Hinton's paper for emergent part-whole hierarchies from data
This is a TensorFlow implementation of the GLOM architecture for creating AI models that understand complex images by breaking them into parts and then understanding how those parts form a whole. You input an image, and it outputs a hierarchy of 'embedding' vectors that represent different levels of detail within that image. AI researchers and deep learning engineers working on advanced computer vision problems would find this useful.
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Use this if you are an AI researcher or deep learning engineer experimenting with novel neural network architectures to better understand hierarchical relationships in visual data.
Not ideal if you are looking for a ready-to-use solution for common computer vision tasks like image classification or object detection.
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37
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5
Language
Python
License
Apache-2.0
Category
Last pushed
Mar 27, 2021
Commits (30d)
0
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