Deep Learning-Based Small Face Detection from Hard Image

Facial detection usually comes first in face recognition and face analysis systems. Previously, techniques such as directed gradient histograms and cascades relied on manually-engineered features from particular photos. Nevertheless, the precision with which these techniques could identify faces in...

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Bibliographic Details
Published inInternational Research Journal on Advanced Engineering Hub (IRJAEH) Vol. 2; no. 3; pp. 579 - 588
Main Authors Sapna Shinde, Priti Chakurkar, Rashmi Rane
Format Journal Article
LanguageEnglish
Published 21.03.2024
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Summary:Facial detection usually comes first in face recognition and face analysis systems. Previously, techniques such as directed gradient histograms and cascades relied on manually-engineered features from particular photos. Nevertheless, the precision with which these techniques could identify faces in uncontrolled environments was restricted. Numerous deep learning-based face recognition frameworks have recently been developed, many of which have significantly increased accuracy, as a result of the rapid progress of deep learning in computer vision. Despite these advancements, detecting small, scaled, positioned, occluded, blurred, and faces that are partially occluded in uncontrolled conditions remains a challenge in face identification. This problem has been studied for many years but has not been completely resolved.
ISSN:2584-2137
2584-2137
DOI:10.47392/IRJAEH.2024.0084