English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Considering the existence of very large amount of available data repositoriesand reach to the very advanced system of hardware, systems meant for facialidentification ave evolved enormously over the past few decades. Sketchrecognition is one of the most important areas that have evolved as an integralcomponent adopted by the agencies of law administration in current trends offorensic science. Matching of derived sketches to photo images of face is alsoa difficult assignment as the considered sketches are produced upon the verbalexplanation depicted by the eye witness of the crime scene and may havescarcity of sensitive elements that exist in the photograph as one canaccurately depict due to the natural human error. Substantial amount of thenovel research work carried out in this area up late used recognition systemthrough traditional extraction and classification models. But very recently,few researches work focused on using deep learning techniques to take anadvantage of learning models for the feature extraction and classification torule out potential domain challenges. The first part of this review paperbasically focuses on deep learning techniques used in face recognition andmatching which as improved the accuracy of face recognition technique withtraining of huge sets of data. This paper also includes a survey on differenttechniques used to match composite sketches to human images which includescomponent-based representation approach, automatic composite sketch recognitiontechnique etc.

A Study on various state of the art of the Art Face Recognition System using Deep Learning Techniques