Abstract
AbstractThe main subject of this publication is to present a selected class of cognitive categorisation systems - understanding based image analysis systems (UBIAS) which support analyses of data recorded in the form of images. Cognitive categorisation systems operate by following particular type of thought, cognitive, and reasoning processes which take place in a human mind and which ultimately lead to making an in-depth description of the analysis and reasoning process. The most important element in this analysis and reasoning process is that it occurs both in the human ability cognitive/thinking process and in the system’s information/reasoning process that conducts the in-depth interpretation and analysis of data.
Subject
Electrical and Electronic Engineering,Radiation,General Materials Science
Reference12 articles.
1. Theoretical aspects of syntactic pattern recogni tion;Tanaka;Pattern Recogn,1995
2. On the linear computational complexity of the parser for quasi context sensitive languages Pattern;Jurek;Recogn Lett,2000
3. Foundations of Intelligent Systems th edited by Zhong Maebashi City Japan;ISMIS;Int Symp,2003
4. Use of random graph parsing for scene labeling by probabilistic relaxation;Skomorowski;Pattern Recogn Lett,1999
5. Medical image segmentation : Auto mated design of border detection criteria from examples Imaging;Brejl;Electron,1999
Cited by
38 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Human Cognition Based Models for Natural and Remote Sensing Image Analysis;Lecture Notes in Electrical Engineering;2023
2. Introduction;Cognitive Information Systems in Management Sciences;2017
3. Security in Management of Distributed Information;Ubiquitous Computing Application and Wireless Sensor;2015
4. Cognitive systems for intelligent business information management in cognitive economy;International Journal of Information Management;2014-12
5. Intelligent Bio-inspired Approach for Secrecy Management in the Cloud;2014 Ninth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing;2014-11