Face Detection Using Open-CV

EasyChair Preprint 10193

Abstract

Face detection in unrestricted conditions has been a trouble for years due to various expressions, brightness, and coloration fringing. Recent studies show that deep learning knowledge of strategies can acquire spectacular performance inside the identification of different gadgets and patterns. This face detection in unconstrained surroundings is difficult due to various poses, illuminations, and occlusions. Figuring out someone with a picture has been popularized through the mass media. However, it's miles less sturdy to fingerprint or retina scanning. The latest research shows that deep mastering techniques can gain mind-blowing performance on those two responsibilities. Face detection in unrestricted conditions has been a trouble for years due to various expressions, brightness, and coloration fringing. Recent studies show that deep learning knowledge of strategies can acquire spectacular performance inside the identification of different gadgets and patterns. This face detection in unconstrained surroundings is difficult due to various poses, illuminations, and occlusions. Figuring out someone with a picture has been popularized through the mass media. However, it's miles less sturdy to fingerprint or retina scanning. The latest research shows that deep mastering techniques can gain mind-blowing performance on those two responsibilities.

Keyphrases: Face Recoginition, Open CV, face detection

@booklet{EasyChair:10193,
  author    = {Lokesh Kumar and Nikhil Singhal and Lakshya Raj Singh Panwar and Mahi Garg},
  title     = {Face Detection Using Open-CV},
  howpublished = {EasyChair Preprint 10193},
  year      = {EasyChair, 2023}}