Unsupervised learning of categories from sets of partially matching image features for power line inspection robot

Proceedings of the International Joint Conference on Neural Networks

Volumn , Issue , 2008, Pages 2596-2603

  Fu, Siyao ^a   Zuo, Qi ^b   Hou, Zeng Guang ^a   Liang, Zize ^a   Tan, Min ^a   Jing, Fengshui ^a   Fu, Xiaoling ^b  

^a INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

^b NORTH CHINA UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTERING METHODS; COMPLEX BACKGROUNDS; COMPUTATIONALLY EFFICIENT; CONSISTENT SUBSETS; FEATURE CORRESPONDENCES; FIELD EXPERIMENTS; IMAGE FEATURES; INSPECTION ROBOTS; LEARNING OBJECTS; LOCAL FEATURES; MATCH ALGORITHMS; POWER LINES; POWERLINE INSPECTIONS; VISION-BASED;

IMAGE ENHANCEMENT; INSPECTION; LEARNING ALGORITHMS; NAVIGATION; OBJECT RECOGNITION; ROBOTICS; ROBOTS;

NEURAL NETWORKS;

EID: 56349144313     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IJCNN.2008.4634161     Document Type: Conference Paper

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