NDLI: GPU based Partially Connected Neural Evolutionary network and its application on gender recognition with face images

Content Provider	IEEE Xplore Digital Library
Author	Xiao-Xi Chen Ming-Hui Shi de Garis, H.
Copyright Year	2010
Description	Author affiliation: Department of Computer Science, Xiamen University, Fujian, China (Xiao-Xi Chen; Ming-Hui Shi; de Garis, H.)
Abstract	An algorithm for evolving neural network via the genetic algorithm based on GPU parallel architecture was implemented on the CUDA, resulting in a system called CuParcone (CUDA based Partially Connected Neural Evolutionary) and was used on gender face recognition. By using the powerful ability of GPU parallel computing, CuParcone achieves a performance increase about 323 times than Parcone algorithm, which runs on a single-processor. With this new model, a gender recognition experiment was made on 530 face images (265 females and 265 males from Color FERET database), including not only frontal faces but also the faces rotated from −40°∼40° in the direction of horizontal, and achieved the accuracy rate of 90.84%.
Starting Page	1930
Ending Page	1934
File Size	807340
Page Count	5
File Format	PDF
ISBN	9781424467129
e-ISBN	9781424467129
DOI	10.1109/WCICA.2010.5554600
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-07
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Graphics processing unit Face Image recognition Face recognition Computational modeling Support vector machines Image color analysis CUDA parallel computing neural networks gender recognition
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Scene image classfying via the Partially Connected Neural Network

CuParcone A High-Performance Evolvable Neural Network Model

Parallel Face Recognition Processing using Neocognitron Neural Network and GPU with CUDA High Performance Architecture

Processing Neocognitron of Face Recognition on High Performance Environment Based on GPU with CUDA Architecture

Parallel computing of WaveCluster algorithm for face recognition application

Parallel Image Processing Based on CUDA

Accelerating the Training of HTK on GPU with CUDA

The Application of CUDA Architecture in Facial Expression Recognition

Artificial Neural Network Simulation on CUDA

GPU based Partially Connected Neural Evolutionary network and its application on gender recognition with face images

Similar Documents

Scene image classfying via the Partially Connected Neural Network

CuParcone A High-Performance Evolvable Neural Network Model

Parallel Face Recognition Processing using Neocognitron Neural Network and GPU with CUDA High Performance Architecture

Processing Neocognitron of Face Recognition on High Performance Environment Based on GPU with CUDA Architecture

Parallel computing of WaveCluster algorithm for face recognition application

Parallel Image Processing Based on CUDA

Accelerating the Training of HTK on GPU with CUDA

The Application of CUDA Architecture in Facial Expression Recognition

Artificial Neural Network Simulation on CUDA

GPU based Partially Connected Neural Evolutionary network and its application on gender recognition with face images