NEURAL NETWORKS FOR REAL TIME DATA EVALUATION IN REMOTE SENSING INSTRUMENTATION

TO INTERPRET, EVALUATE, AND ANALYZE DATA FROM REMOTE-SENSING, MULTISPECTRAL INSTRUMENTATION IN REAL OR NEAR-REAL TIME IS THE GOAL OF THIS PROJECT. THIS SYSTEM WILL BE ADAPTIVE BY LEARNING TO INTERPRET APPLICATION-SPECIFIC FEATURES. BASED ON NEURAL-NETWORK TECHNOLOGY, IT WILL FOCUS ON PATTERNS FOUND IN THE DATA REGARDLESS OF THE IRRELEVANT VARIATIONS OF INTENSITY, MAGNIFICATION, CLUTTER, OR NOISE. THE SYSTEM SHOULD BE COMPATIBLE WITH DEPLOYMENT IN LIGHT AIRCRAFT OR BALLOONS FOR INTERDISCIPLINARY RESEARCH ACTIVITIES. IN PHASE I THIS PROJECT WILL DESIGN, DEVELOP, AND TEST GROUPS OF INTERRELATED NEURAL NETWORKS TO INTERPRET DATA FROM DIFFERENT SPECTRAL BANDS. THE INTERPRETATION OF NETWORK-FUSED DATA FROM VARIOUS SPECTRAL BANDS (0.4-14.0 MICROMETERS) WILL BE SIMULATED AS A PROOF-OF-CONCEPT WITH A SIMPLE PROBLEM. NEURAL-NETWORK HARDWARE WILL BE REVIEWED TO IDENTIFY COMPATIBLE ELECTRONICSFOR THE ADAPTIVE, REAL-TIME, MULTIPLE-NETWORK SYSTEM RECOMMENDED HERE. TO INTERPRET, EVALUATE, AND ANALYZE DATA FROM REMOTE-SENSING, MULTISPECTRAL INSTRUMENTATION IN REAL OR NEAR-REAL TIME IS THE GOAL OF THIS PROJECT. THIS SYSTEM WILL BE ADAPTIVE BY LEARNING TO INTERPRET APPLICATION-SPECIFIC FEATURES. BASED ON NEURAL-NETWORK TECHNOLOGY, IT WILL FOCUS ON PATTERNS FOUND IN THE DATA REGARDLESS OF THE IRRELEVANT VARIATIONS OF INTENSITY, MAGNIFICATION, CLUTTER, OR NOISE. THE SYSTEM SHOULD BE COMPATIBLE WITH DEPLOYMENT IN LIGHT AIRCRAFT OR BALLOONS FOR INTERDISCIPLINARY RESEARCH ACTIVITIES. IN PHASE I THIS PROJECT WILL DESIGN, DEVELOP, AND TEST GROUPS OF INTERRELATED NEURAL NETWORKS TO INTERPRET DATA FROM DIFFERENT SPECTRAL BANDS. THE INTERPRETATION OF NETWORK-FUSED DATA FROM VARIOUS SPECTRAL BANDS (0.4-14.0 MICROMETERS) WILL BE SIMULATED AS A PROOF-OF-CONCEPT WITH A SIMPLE PROBLEM. NEURAL-NETWORK HARDWARE WILL BE REVIEWED TO IDENTIFY COMPATIBLE ELECTRONICSFOR THE ADAPTIVE, REAL-TIME, MULTIPLE-NETWORK SYSTEM RECOMMENDED HERE.