caa a22 4500 467944733 CHVBK 20180323165659.0 cr unu---uuuuu 170328e19901001xx s 000 0 eng 10.1007/BF00116879 doi (NATIONALLICENCE)springer-10.1007/BF00116879 (NATIONALLICENCE)springer-10.1023/A:1022633824867 Montana David Bolt, Beranek and Newman, Inc., 70 Fawcett Street, 02138, Cambridge, MA aut Empirical learning using rule threshold optimization for detection of events in synthetic images [Elektronische Daten] [David Montana] We have developed an expert system for interpretation of passive sonar images. A key component of the system is a group of event detection rules whose conditions consist of tests against thresholds. Due to the complexity, variability and clumpiness (i.e., tendency towards highly nonuniform distribution) of the data, tuning these thresholds for good performance under all conditions is a difficult task. We have implemented a procedure for learning rule thresholds whereby the detection capability of each rule continually improves as more and more data is played through the system. The learning procedure contains the following components: 1) a windowing mechanism that adds exceptions (i.e., false alarms and missed detections) into a training database of positive and negative examples and 2) a genetic algorithm to optimize the thresholds with respect to the training database. The genetic training algorithm allows the developer to explicitly choose an operating point on the Receiver Operating Characteristic (ROC) curve of a rule. Experiments have verified 1) the superiority of this automated approach to selecting rule thresholds over manual techniques and 2) the improvement of rule performance with experience. Kluwer Academic Publishers, 1990 Learning nationallicence image interpretation nationallicence detection nationallicence optimization nationallicence genetic algorithms nationallicence thresholded rules nationallicence Machine Learning Kluwer Academic Publishers 5/4(1990-10-01), 427-450 0885-6125 5:4<427 1990 5 10994 https://doi.org/10.1007/BF00116879 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/BF00116879 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Montana David Bolt, Beranek and Newman, Inc., 70 Fawcett Street, 02138, Cambridge, MA aut NATIONALLICENCE 773 0- Machine Learning Kluwer Academic Publishers 5/4(1990-10-01), 427-450 0885-6125 5:4<427 1990 5 10994 NATIONALLICENCE 856 40 https://doi.org/10.1023/A:1022633824867 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Montana David Bolt, Beranek and Newman, Inc., 70 Fawcett Street, 02138., Cambridge, MA aut NATIONALLICENCE 773 0- Machine Learning Kluwer Academic Publishers-Plenum Publishers 5/4(1990-10-01), 427-450 0885-6125 5:4<427 1990 5 10994 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE NATIONALLICENCE NL-springer