A new pattern associative memory model for image recognition based on Hebb rules and dot product

Mingyue Gao; Limiao Deng; Yanjiang Wang

doi:10.1117/12.2302483

10 April 2018 A new pattern associative memory model for image recognition based on Hebb rules and dot product

Mingyue Gao, Limiao Deng, Yanjiang Wang

Proceedings Volume 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017); 1061512 (2018) https://doi.org/10.1117/12.2302483
Event: Ninth International Conference on Graphic and Image Processing, 2017, Qingdao, China

Abstract

A great number of associative memory models have been proposed to realize information storage and retrieval inspired by human brain in the last few years. However, there is still much room for improvement for those models. In this paper, we extend a binary pattern associative memory model to accomplish real-world image recognition. The learning process is based on the fundamental Hebb rules and the retrieval is implemented by a normalized dot product operation. Our proposed model can not only fulfill rapid memory storage and retrieval for visual information but also have the ability on incremental learning without destroying the previous learned information. Experimental results demonstrate that our model outperforms the existing Self-Organizing Incremental Neural Network (SOINN) and Back Propagation Neuron Network (BPNN) on recognition accuracy and time efficiency.

Citation Download Citation

Mingyue Gao, Limiao Deng, and Yanjiang Wang "A new pattern associative memory model for image recognition based on Hebb rules and dot product", Proc. SPIE 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017), 1061512 (10 April 2018); https://doi.org/10.1117/12.2302483

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available