Learning to count with deep object features

IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

Volumn 2015-October, Issue , 2015, Pages 90-96

  Segui, Santi ^a,b   Pujol, Oriol ^a,b   Vitria, Jordi ^a,b  

^a UNIVERSITY OF BARCELONA   (Spain)

^b Barcelona Perception Computing Lab   (Spain)

Author keywords

Accuracy; Feature extraction; Neural networks; Proposals; Supervised learning; Training; Visualization

Indexed keywords

COMPUTER VISION; DEEP LEARNING; FLOW VISUALIZATION; NEURAL NETWORKS; OBJECT DETECTION; PERSONNEL TRAINING; SUPERVISED LEARNING;

ACCURACY; CONVOLUTIONAL NEURAL NETWORK; COUNTING PROBLEMS; FINAL OBJECTIVE; INDIVIDUAL OBJECTS; INTERNAL REPRESENTATION; LEARNING STRATEGY; PROPOSALS;

FEATURE EXTRACTION;

EID: 84951956461     PISSN: 21607508     EISSN: 21607516     Source Type: Conference Proceeding    
DOI: 10.1109/CVPRW.2015.7301276     Document Type: Conference Paper

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