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Record Details

Record 28 of 5586
Neural Network Target Identification System for False Alarm Reduction
External Online Source: hdl:2014/44621
Author and Affiliation:
Ye, David(California Inst. of Tech., Pasadena, CA, United States)
Edens, Weston(Butler Univ., Indianapolis, IN, United States)
Lu, Thomas T.(Jet Propulsion Lab., California Inst. of Tech., Pasadena, CA, United States)
Chao, Tien-Hsin(Jet Propulsion Lab., California Inst. of Tech., Pasadena, CA, United States)
Abstract: A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feed forward back propagation neural network (NN) is then trained to classify each feature vector and remove false positives. This paper discusses the test of the system performance and parameter optimizations process which adapts the system to various targets and datasets. The test results show that the system was successful in substantially reducing the false positive rate when tested on a sonar image dataset.
Publication Date: Apr 13, 2009
Document ID:
20150008328
(Acquired May 20, 2015)
Subject Category: CYBERNETICS, ARTIFICIAL INTELLIGENCE AND ROBOTICS
Document Type: Conference Paper
Meeting Information: SPIE Defense, Security and Sensing; 13-17 Apr. 2009; Orlando. FL; United States
Meeting Sponsor: International Society for Optical Engineering; Bellingham, WA, United States
Financial Sponsor: Jet Propulsion Lab., California Inst. of Tech.; Pasadena, CA, United States
Organization Source: Jet Propulsion Lab., California Inst. of Tech.; Pasadena, CA, United States
Description: 11p; In English
Distribution Limits: Unclassified; Publicly available; Unlimited
Rights: Copyright
NASA Terms: NEURAL NETS; TARGET RECOGNITION; FALSE ALARMS; COMPUTER VISION; FEEDFORWARD CONTROL; BACKPROPAGATION (ARTIFICIAL INTELLIGENCE); ALGORITHMS; WAVELET ANALYSIS; SONAR; TRANSFORMATIONS (MATHEMATICS); DETECTION; COMPUTERIZED SIMULATION
Other Descriptors: ATR; RECOGNITION
Availability Source: Other Sources
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