slugPerformance Enhancement Over Wireless Mobile Adhoc Network

Abstract

face detection research confronts the full range of challenges found in general purpose, object class recognition. However, the class of faces also has very apparent regularities that are exploited by many heuristic or model - based methods or are readily “ learned” in data - driven methods. One expects some regularity when defining classes in general, but they may not be so apparent. Finally, though faces have tremendous within - class variability, face detection remains a two class recognition problem (face versus non face). The system correctly classified expressions for each individual using only still images. It distinguishes 3 expressions (Happiness (HA), surprise, anger, and fear) precisely and identifies 1 other, Happiness by the Average Recognition Rate accuracy of 85.25%. Also many people made mistake identifying surprise from happiness. According to Carlo research Surprise is mis - recognized as happy. Following this information, Output membership functions are built and clearly depicted some expressions d ue to the mentioned facts. Experimental results demonstrate the superiority of the proposed method to existing ones.

Authors and Affiliations

Ajeet Kumar Mishra, Anil Kumar Sharma, Dr. S. K. Shrivastava

Keywords

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  • EP ID EP18040
  • DOI -
  • Views 285
  • Downloads 13

How To Cite

Ajeet Kumar Mishra, Anil Kumar Sharma, Dr. S. K. Shrivastava (2014). slugPerformance Enhancement Over Wireless Mobile Adhoc Network. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 2(5), -. https://europub.co.uk/articles/-A-18040