Detection of unexploded ordnance via efficient semisupervised and active learning

IEEE Transactions on Geoscience and Remote Sensing

Volumn 46, Issue 9, 2008, Pages 2558-2567

  Liu, Qiuhua ^a,b,c   Liao, Xuejun ^a,b   Carin, Lawrence ^a,b  

^a IEEE

^b Duke University   (United States)

^c SCHLUMBERGER DOLL RESEARCH   (United States)

Author keywords

Detectors; Electromagnetic induction (EMI)

Indexed keywords

ALGORITHMS; CLASSIFICATION (OF INFORMATION); CLASSIFIERS; CRACK INITIATION; EDUCATION; ELECTROMAGNETIC INDUCTION; ELECTROMAGNETISM; EXCAVATION; GRAPH THEORY; KNOWLEDGE BASED SYSTEMS; LABELING; LABELS; LEARNING SYSTEMS; MAGNETISM; MILITARY EQUIPMENT; ORDNANCE; PROBABILITY; PROJECTILES; RANDOM PROCESSES; RISK ASSESSMENT; SCADA SYSTEMS; SENSORS;

ACTIVE LEARNING; CLASSIFICATION RESULTS; CLASSIFIER DESIGNS; DETECTORS; ELECTROMAGNETIC INDUCTION (EMI); GRAPH-BASED; LABELED AND UNLABELED DATA; LABELED DATA; LEARNING PHASE; LEARNING PROCEDURES; MUTUAL INFORMATION; SEMI-SUPERVISED LEARNING; SENSOR DATA; SUPERVISED ALGORITHMS; UNEXPLODED ORDNANCE; UNLABELED DATA;

LEARNING ALGORITHMS;

ALGORITHMS; CLASSIFICATION; CLASSIFIERS; DETECTORS; EDUCATION; ELECTROMAGNETIC FIELDS; LABELING; LABELS; MAGNETIC PROPERTIES; PROBABILITY; PROJECTILES; RANDOM PROCESSES; RISK ASSESSMENT; SENSORS; WEAPONS;

EID: 50549095916     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2008.920468     Document Type: Conference Paper

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