A Study on various state of the art of the Art Face Recognition System using Deep Learning Techniques
Sukhada Chokkadi, Sannidhan M S, Sudeepa K B, Abhir Bhandary

TL;DR
This paper reviews the advancements in face recognition systems, emphasizing deep learning techniques that improve accuracy and discusses methods for matching sketches to facial images.
Contribution
It provides a comprehensive survey of deep learning applications in face recognition and sketch matching, highlighting recent improvements and methodologies.
Findings
Deep learning enhances face recognition accuracy with large datasets.
Survey covers various sketch-to-face matching techniques.
Recent methods outperform traditional recognition models.
Abstract
Considering the existence of very large amount of available data repositories and reach to the very advanced system of hardware, systems meant for facial identification ave evolved enormously over the past few decades. Sketch recognition is one of the most important areas that have evolved as an integral component adopted by the agencies of law administration in current trends of forensic science. Matching of derived sketches to photo images of face is also a difficult assignment as the considered sketches are produced upon the verbal explanation depicted by the eye witness of the crime scene and may have scarcity of sensitive elements that exist in the photograph as one can accurately depict due to the natural human error. Substantial amount of the novel research work carried out in this area up late used recognition system through traditional extraction and classification models. But…
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