On the location dependence of convolutional neural network features

IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

Volumn 2015-October, Issue , 2015, Pages 70-78

  Workman, Scott ^a   Jacobs, Nathan ^a  

^a UNIVERSITY OF KENTUCKY   (United States)

Author keywords

Databases; Feature extraction; Geology; Neural networks; Principal component analysis; Support vector machines; Visualization

Indexed keywords

AERIAL PHOTOGRAPHY; ANTENNAS; BENCHMARKING; COMPUTER VISION; CONVOLUTION; DATABASE SYSTEMS; EXTRACTION; FEATURE EXTRACTION; FLOW VISUALIZATION; GEOLOGY; LARGE DATASET; NEURAL NETWORKS; PRINCIPAL COMPONENT ANALYSIS; SUPPORT VECTOR MACHINES; WIDE AREA NETWORKS;

COMPUTER VISION APPLICATIONS; CONVOLUTIONAL NETWORKS; CONVOLUTIONAL NEURAL NETWORK; DISCRIMINATIVE ABILITY; HIGH-LEVEL FEATURES; IMAGE LOCALIZATION; REGION IDENTIFICATION; STATE-OF-THE-ART PERFORMANCE;

MULTILAYER NEURAL NETWORKS;

EID: 84951997011     PISSN: 21607508     EISSN: 21607516     Source Type: Conference Proceeding    
DOI: 10.1109/CVPRW.2015.7301385     Document Type: Conference Paper

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