SKIN DISEASE IMAGE RECOGNITION USING K-NN ALGORITHM AND DEEP LEARNING USING FLASK FRAMEWORK.
In the field the human face is an important entity which plays a crucial role in our daily social interaction, like conveying individual's identity. Face recognition system is also able to recognize the person from a distance without touching or any interaction with the person. Currently, face recog...
| Publicado en: | Turkish Journal of Physiotherapy Rehabilitation Vol. 32; no. 2; pp. 2227 - 2233 |
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| Autores principales: | , , , , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
Turkish Journal of Physiotherapy & Rehabilitation
2021
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=151006225&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 151006225 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 13008757 YU1 jtl: Turkish Journal of Physiotherapy Rehabilitation issn: 13008757 maglogo: N pubinfo: dt: 2021 vid: 32 iid: 2 pid: 20392 pub: Turkish Journal of Physiotherapy & Rehabilitation place: Kizilay/ Ankara, <Blank> artinfo: ui: 151006225 151006225 151006225 151006225 ppf: 2227 ppct: 6 formats: fmt: @attributes: type: P tig: atl: SKIN DISEASE IMAGE RECOGNITION USING K-NN ALGORITHM AND DEEP LEARNING USING FLASK FRAMEWORK. aug: au: ELANKEERTHANA, R. SUJITHA, P. SAFRIN, S. PREETHIKA, M. SHALINI, M. affil: Assistant Professor, M.Kumarasamy College Of Engineering, Tamil Nadu, India sug: subj: Skin Diseases Deep Learning Diagnostic Imaging Human Algorithms Image Processing, Computer Assisted Neural Networks (Computer) ab: In the field the human face is an important entity which plays a crucial role in our daily social interaction, like conveying individual's identity. Face recognition system is also able to recognize the person from a distance without touching or any interaction with the person. Currently, face recognition applications are deployed in social media websites like Facebook, in the entrance of Airports, Railways Stations, Bus Stop, highly secured areas, advertisement, and health care. The purpose of these applications is to minimize criminal activities, fake authentication, tracking addictive gamblers in casinos, whereas Facebook is using face recognition system for automatic tagging purpose. For face recognition purpose, there is a need for large data sets and complex features to uniquely identify the different subjects by manipulating different obstacles like illumination, pose and aging.in this project we proposes a deep unified model for Face Recognition based on Faster Region Convolution Neural Network. Design a group-based face attendance system based on the proposed deep unified model. In our proposed system, we have a number of class rooms of a specific institute in which we setup our face recognition system for making a smart class rooms. Several images from different smart class room Buffys are being sent simultaneously for processing, in order to take the attendance. In order to measure the validity of the proposed algorithm, a web application of a group based face attendance system is developed. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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