DocumentCode
1863556
Title
Recognizing Adult Image Groups for Web Site Classification
Author
Sun, Hung-Ming
Author_Institution
Dept. of Comput. Sci. & Inf. Eng., Kainan Univ., Luchu, Taiwan
fYear
2010
fDate
9-10 Jan. 2010
Firstpage
302
Lastpage
305
Abstract
The recognition accuracy of adult image groups depends on the performance of the adult image recognizer and the final decision rule. Earlier methods of recognizing adult image groups do not take into account the performance tuning of the adult image recognizer but only focus on the decision rule. The proposed method considers the two factors together and resolves optimal parameter settings to achieve the best recognition accuracy for image groups. Experimental results show that the proposed method can attain higher recognition accuracy than the earlier methods.
Keywords
Web sites; image classification; Web site classification; adult image groups; adult image recognizer; decision rule; optimal parameter settings; recognition accuracy; Data mining; Feature extraction; Image databases; Image recognition; Image retrieval; Image segmentation; Neural networks; Skin; Sun; Testing; adult image recognition; image group classification; neural network; web site classification;
fLanguage
English
Publisher
ieee
Conference_Titel
Knowledge Discovery and Data Mining, 2010. WKDD '10. Third International Conference on
Conference_Location
Phuket
Print_ISBN
978-1-4244-5397-9
Electronic_ISBN
978-1-4244-5398-6
Type
conf
DOI
10.1109/WKDD.2010.41
Filename
5432616
Link To Document