Human detection and activity classification based on micro-doppler signatures using deep convolutional neural networks

IEEE Geoscience and Remote Sensing Letters

Volumn 13, Issue 1, 2016, Pages 8-12

  Kim, Youngwook ^a   Moon, Taesup ^b  

^a CALIFORNIA STATE UNIVERSITY   (United States)

^b Daegu Gyeongbuk Institute of Science and Technology   (South Korea)

Author keywords

Convolutional neural network; Deep learning; Human activity classification; Human detection; Micro Doppler

Indexed keywords

CONVOLUTION; DOPPLER RADAR; LEARNING ALGORITHMS; NEURAL NETWORKS;

ACTIVITY CLASSIFICATIONS; CLASSIFICATION BOUNDARY; CONVOLUTIONAL NEURAL NETWORK; DEEP LEARNING; DOMAIN KNOWLEDGE; HIGH-ACCURACY; HUMAN ACTIVITIES; HUMAN DETECTION;

CLASSIFICATION (OF INFORMATION);

EID: 84946811871     PISSN: 1545598X     EISSN: None     Source Type: Journal    
DOI: 10.1109/LGRS.2015.2491329     Document Type: Article

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