Open AccessASSOCIATIVE MEMORIES NETWORK FOR FACE RECOGNITION AND OBJECT RECOGNITION
Author(s) -
Roberto A. Vázquez,
Humberto Sossa
Publication year - 2014
Publication title -
computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.184
H-Index - 11
eISSN - 2312-5381
pISSN - 1727-6209
DOI - 10.47839/ijc.8.1.656
Subject(s) - computer science , associative property , content addressable memory , pattern recognition (psychology) , bidirectional associative memory , artificial intelligence , artificial neural network , task (project management) , face (sociological concept) , object (grammar) , recall , simple (philosophy) , image (mathematics) , facial recognition system , computer vision , mathematics , social science , linguistics , philosophy , management , epistemology , sociology , pure mathematics , economics
An associative memory (AM) is a special kind of neural network that allows associating an output pattern with an input pattern. Some problems require associating several output patterns with a unique pattern. Classical associative and neural models cannot solve this simple task and less if these patterns are complex images, for example faces. In this paper a network of AMs to recall a collection of patterns is proposed. The accuracy of the proposal is tested with two benchmarks. One is composed by 20 objects and the other is composed by 20 images of 15 different people faces. First the all, the benchmarks are split into several collections and then this collections are used to train the network of AMs. During training an image of a collection is associated with the rest of the images belonging to the same collection. Once trained the network we expected to recover a collection of images by using as an input pattern any image belonging to the collection.