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CUDA-based parallelization of a bio-inspired model for fast object classification.
- Source :
-
Neural Computing & Applications . Nov2018, Vol. 30 Issue 10, p3007-3018. 12p. - Publication Year :
- 2018
-
Abstract
- The need for highly accurate classification systems capable of working on real-time applications has increased in recent years. Nowadays, several computer vision tasks apply a classification step as part of bigger systems, hence requiring classification models that work at a fast pace. This rendered interesting the concept of real-time object classification to several research communities. In this paper, we propose to accelerate a bio-inspired model for object classification, which has given very good results when compared with other state-of-the-art proposals using the compute unified device architecture (CUDA) and exploiting computational capabilities of graphic processing units. The classification model that is used is called the artificial visual cortex, a novel bio-inspired approach for image classification. In this work, we show that through an implementation of this model in the CUDA framework it is possible to achieve real-time functionality. As a result, the proposed system is able to process images in average of up to 90 times faster than the original system. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09410643
- Volume :
- 30
- Issue :
- 10
- Database :
- Academic Search Index
- Journal :
- Neural Computing & Applications
- Publication Type :
- Academic Journal
- Accession number :
- 132879637
- Full Text :
- https://doi.org/10.1007/s00521-017-2873-3