A fast object recognizer with a very small number of information using human cognitive-inspired computation model

Arwin D. W. Sumari; Rosa A. Asmara; Dimas R. H. Putra; Ika N. Syamsiana

doi:10.1117/12.2618805

31 May 2022 A fast object recognizer with a very small number of information using human cognitive-inspired computation model

Arwin D. W. Sumari, Rosa A. Asmara, Dimas R. H. Putra, Ika N. Syamsiana

Author Affiliations +

Proceedings Volume 12124, Unmanned Systems Technology XXIV; 121240G (2022) https://doi.org/10.1117/12.2618805
Event: SPIE Defense + Commercial Sensing, 2022, Orlando, Florida, United States

Abstract

Human at every age, can recognize any kind of object very easily even at a short time just by observing it. Recognizing an object has been a challenge for a machine since the introduction of a computation model that mimics how brain’s neurons work more than 70 years ago. The invention of artificial neural network especially its derivative namely deep learning has improved the performance of an intelligent machine’s object recognition. However, the training scheme that is a part of neural network-based learning methodology requires other efforts such as providing a huge number of data along with their annotation that impacts to the need of high-performance computing equipment. Faced to the need of an object recognizer that requires just a small number of information, light computing, and can be deployed quickly without the hassle of doing any training, we propose a fast object recognizer inspired by human cognitive computation called as Knowledge Growing System (KGS) which is a model of Cognitive Artificial Intelligence. By using the Iris dataset, the one that has been proven as test data for years, we proved that KGS can obtain an accuracy of 85.93 % in average by only observing a small number of information, that is only 15 data out of 150 or 10%. Based on this result, we plan to extend KGS to recognize more complex objects such as airplanes and unmanned vehicles.

Conference Presentation

Citation Download Citation

Arwin D. W. Sumari, Rosa A. Asmara, Dimas R. H. Putra, and Ika N. Syamsiana "A fast object recognizer with a very small number of information using human cognitive-inspired computation model", Proc. SPIE 12124, Unmanned Systems Technology XXIV, 121240G (31 May 2022); https://doi.org/10.1117/12.2618805

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