Training object detection and recognition CNN models using data augmentation

IS and T International Symposium on Electronic Imaging Science and Technology

Volumn , Issue , 2017, Pages 27-36

  Montserrat, Daniel Mas ^a   Lin, Qian ^b   Allebach, Jan ^a   Delp, Edward J ^a  

^a PURDUE UNIVERSITY   (United States)

^b HEWLETT PACKARD LABORATORIES   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DEEP LEARNING; DEFORMATION; FEATURE EXTRACTION; GLOBAL SYSTEM FOR MOBILE COMMUNICATIONS; MATHEMATICAL TRANSFORMATIONS; NEURAL NETWORKS; OBJECT RECOGNITION; SEMANTICS;

CONVOLUTIONAL NEURAL NETWORK; DATA AUGMENTATION; DETECTING OBJECTS; NONLINEAR TRANSFORMS; OBJECT DETECTION AND RECOGNITION; TECHNICAL CHALLENGES; TRAINING DATASET; TRAINING OBJECTS;

OBJECT DETECTION;

EID: 85030256427     PISSN: None     EISSN: 24701173     Source Type: Conference Proceeding    
DOI: 10.2352/ISSN.2470-1173.2017.10.IMAWM-163     Document Type: Conference Paper

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