Detection of small man-made objects in sector scan imagery using neural networks

Oceans Conference Record (IEEE)

Volumn 4, Issue , 2001, Pages 2108-2114

  Perry, Stuart W ^a   Guan, Ling ^b  

^a DEFENCE SCIENCE AND TECHNOLOGY ORGANISATION   (Australia)

^b RYERSON UNIVERSITY   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ACOUSTIC NOISE; CORRELATION METHODS; FEATURE EXTRACTION; IMAGE SEGMENTATION; MOTION COMPENSATION; NEURAL NETWORKS; SHIPS; SIGNAL DETECTION;

CROSS-CORRELATION TECHNIQUE; FORWARD-LOOKING SONAR SYSTEM; MAN-MADE OBJECT; SECOND-ORDER HISTOGRAM; SECTOR SCAN IMAGERY; SEQUENTIAL BACKWARD SELECTION; SEQUENTIAL FORWARD SELECTION;

SONAR;

EID: 0035672380     PISSN: 01977385     EISSN: None     Source Type: Journal    
DOI: 10.1109/OCEANS.2001.968325     Document Type: Article

References (14)

1. An adaptive underwater target classification system
2. Adaptive nonstationary filtering procedure for sea mine classification
3. Objects classification using neural network in sonar imagery
4. A voting-based approach for fast object recognition in underwater acoustic images
5. Detection and tracking of returns in sector-scan sonar image sequences
6. A comparison of inter-frame feature measures for robust object classification in sector scan sonar image sequences
7. A general regression neural network
8. Shape analysis of mammographic calcifications
9. Textural features for image classification
10. A direct adaptive method for faster backpropagation learning: The RPROP algorithm