Glimpse, a General Layer-wise IMage ProceSsing Engine
The Glimpse project [IJCNN2013] is a library for implementing hierarchical visual models in C++ and Python. The goal of this project is to allow a broad range of feed-forward, hierarchical models to be encoded in a high-level declarative manner, with low-level details of the implementation hidden from view. This project combines an efficient implementation with the ability to leverage parallel processing facilities and is designed to run on multiple operating systems using only common, freely-available components. A prototype of Glimpse has been used to encode an HMAX-like model, achieving results comparable with those found in the literature. The project has been supported by NSF Grant 1018967 (PIs: Melanie Mitchell and Garrett Kenyon).
Source code and documentation are available for the project, as well as an installable package.
Michael D. Thomure, Melanie Mitchell, Garrett T. Kenyon (2013). On the Role of Shape Prototypes in Hierarchical Models of Vision. To appear in The International Joint Conference on Neural Networks (IJCNN).
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Release files for glimpse 0.2.1
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