FACE RECOGNITION USING DEEP LEARNING XCEPTION CNN METHOD

Autor: PALLAVARAM VENKATESWAR LAL, UPPALAPATI SRILAKSHMI, D.VENKATESWARLU
Jazyk: angličtina
Rok vydání: 2022
Předmět:
DOI: 10.5281/zenodo.6009096
Popis: The continual development of computer vision technology is one of the main research paths in the area of computer vision during recent years. It detects, tracks, recognizes, or authenticates human appearances from any picture or video taken through a digital camera and provides accurate and quick enough recognition functions for commercial use. Widely utilized in mobile payments, safe cities, criminal investigations, and other areas. Much research has progressed into face detection, identification and safety, the main problems are the consideration of those objects that had "different sizes" and "different aspects ratios" in a single framework that prevented or exceeded human level accuracy in human face appearance, such as noise in face images, opposite illumination,,Haar cascade was found to produce optimum accuracy while analyzing the multi focus faces using FERET database and the LFW database, and utilizes Xception (Depth Wise Separable). CNN is used for extracting the feature. Finally, classification is carried out. The suggested approach obtained FERET accuracy by about 96.73%, and LFW data by approximately 98.45%. The research findings have shown that the predicted technique exceeds existing methods.
Databáze: OpenAIRE