Authors
Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jonathon Shlens, Zbigniew Wojna
Publication date
2015/12/2
Journal
arXiv preprint arXiv:1512.00567
Description
Abstract: Convolutional networks are at the core of most state-of-the-art computer vision
solutions for a wide variety of tasks. Since 2014 very deep convolutional networks started to
become mainstream, yielding substantial gains in various benchmarks. Although increased
model size and computational cost tend to translate to immediate quality gains for most tasks
(as long as enough labeled data is provided for training), computational efficiency and low
parameter count are still enabling factors for various use cases such as mobile vision and ...
solutions for a wide variety of tasks. Since 2014 very deep convolutional networks started to
become mainstream, yielding substantial gains in various benchmarks. Although increased
model size and computational cost tend to translate to immediate quality gains for most tasks
(as long as enough labeled data is provided for training), computational efficiency and low
parameter count are still enabling factors for various use cases such as mobile vision and ...
Total citations
Scholar articles
C Szegedy, V Vanhoucke, S Ioffe, J Shlens, Z Wojna - arXiv preprint arXiv:1512.00567, 2015
Dates and citation counts are estimated and are determined automatically by a computer program.