Article

Face Detection Using GPU-Based Convolutional Neural Networks

Authors:

Fabian Nasse,

Christian Thurau,

Gernot A. FinkAuthors Info & Claims

CAIP '09: Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns

Pages 83 - 90

https://doi.org/10.1007/978-3-642-03767-2_10

Published: 29 August 2009 Publication History

Abstract

In this paper, we consider the problem of face detection under pose variations. Unlike other contributions, a focus of this work resides within efficient implementation utilizing the computational powers of modern graphics cards. The proposed system consists of a parallelized implementation of convolutional neural networks (CNNs) with a special emphasize on also parallelizing the detection process. Experimental validation in a smart conference room with 4 active ceiling-mounted cameras shows a dramatic speed-gain under real-life conditions.

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Ning LWang JLiu R(2024)Research on Digital Transformation and Upgrading of University Engineering Technology Majors based on Neural NetworkProceeding of the 2024 5th International Conference on Computer Science and Management Technology10.1145/3708036.3708200(995-997)Online publication date: 18-Oct-2024
https://dl.acm.org/doi/10.1145/3708036.3708200
Sanchez JSoltani NKulkarni PChamarthi RTabkhi H(2018)A Reconfigurable Streaming Processor for Real-Time Low-Power Execution of Convolutional Neural Networks at the EdgeEdge Computing – EDGE 201810.1007/978-3-319-94340-4_4(49-64)Online publication date: 25-Jun-2018
https://dl.acm.org/doi/10.1007/978-3-319-94340-4_4
Jafri R(2017)A GPU-accelerated real-time contextual awareness application for the visually impaired on Google's project Tango deviceThe Journal of Supercomputing10.1007/s11227-016-1891-873:2(887-899)Online publication date: 1-Feb-2017
https://dl.acm.org/doi/10.1007/s11227-016-1891-8
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Face Detection Using GPU-Based Convolutional Neural Networks
1. Computing methodologies
  1. Machine learning
    1. Machine learning approaches

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CAIP '09: Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns

August 2009

1244 pages

ISBN:9783642037665

Editors:
Xiaoyi Jiang
Department of Mathematics and Computer Science, University of Münster, Münster, Germany 48149
,
Nicolai Petkov
Institute of Mathematics and Computing Science, University of Groningen, Groningen, The Netherlands 9747

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 29 August 2009

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Ning LWang JLiu R(2024)Research on Digital Transformation and Upgrading of University Engineering Technology Majors based on Neural NetworkProceeding of the 2024 5th International Conference on Computer Science and Management Technology10.1145/3708036.3708200(995-997)Online publication date: 18-Oct-2024
https://dl.acm.org/doi/10.1145/3708036.3708200
Sanchez JSoltani NKulkarni PChamarthi RTabkhi H(2018)A Reconfigurable Streaming Processor for Real-Time Low-Power Execution of Convolutional Neural Networks at the EdgeEdge Computing – EDGE 201810.1007/978-3-319-94340-4_4(49-64)Online publication date: 25-Jun-2018
https://dl.acm.org/doi/10.1007/978-3-319-94340-4_4
Jafri R(2017)A GPU-accelerated real-time contextual awareness application for the visually impaired on Google's project Tango deviceThe Journal of Supercomputing10.1007/s11227-016-1891-873:2(887-899)Online publication date: 1-Feb-2017
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Holden DSaito JKomura TJoyce T(2015)Learning motion manifolds with convolutional autoencodersSIGGRAPH Asia 2015 Technical Briefs10.1145/2820903.2820918(1-4)Online publication date: 2-Nov-2015
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Majumdar ACadambi SBecchi MChakradhar SGraf H(2012)A Massively Parallel, Energy Efficient Programmable Accelerator for Learning and ClassificationACM Transactions on Architecture and Code Optimization10.1145/2133382.21333889:1(1-30)Online publication date: 1-Mar-2012
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Di Salvo RPino C(2011)Image and video processing on CUDAProceedings of the 13th WSEAS international conference on Mathematical and computational methods in science and engineering10.5555/2074857.2074871(60-66)Online publication date: 3-Nov-2011
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Cadambi SMajumdar ABecchi MChakradhar SGraf HSalapura VGschwind MKnoop J(2010)A programmable parallel accelerator for learning and classificationProceedings of the 19th international conference on Parallel architectures and compilation techniques10.1145/1854273.1854309(273-284)Online publication date: 11-Sep-2010
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Chakradhar SSankaradas MJakkula VCadambi S(2010)A dynamically configurable coprocessor for convolutional neural networksACM SIGARCH Computer Architecture News10.1145/1816038.181599338:3(247-257)Online publication date: 19-Jun-2010
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