FCN-rLSTM: Deep Spatio-Temporal Neural Networks for Vehicle Counting in City Cameras

Proceedings of the IEEE International Conference on Computer Vision

Volumn 2017-October, Issue , 2017, Pages 3687-3696

  Zhang, Shanghang ^a,b   Wu, Guanhang ^a   Costeira, Joao P ^b   Moura, Jose M F ^a  

^a CARNEGIE MELLON UNIVERSITY   (United States)

^b UNIVERSITY OF LISBON   (Portugal)

Author keywords

[No Author keywords available]

Indexed keywords

CAMERAS; COMPUTER VISION; CONVOLUTION; DEEP NEURAL NETWORKS; MOBILE TELECOMMUNICATION SYSTEMS; NEURAL NETWORKS; PIXELS; VEHICLES;

CONVOLUTIONAL NEURAL NETWORK; FEATURE REPRESENTATION; MEAN ABSOLUTE ERROR; RESIDUAL FUNCTIONS; SHORT TERM MEMORY; TEMPORAL DYNAMICS; TEMPORAL INFORMATION; TRAINING PROCESS;

LONG SHORT-TERM MEMORY;

EID: 85041892348     PISSN: 15505499     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2017.396     Document Type: Conference Paper

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