An effective face recognition system based on Cloud based IoT with a deep learning model
- Title
- An effective face recognition system based on Cloud based IoT with a deep learning model
- Creator
- Chauhan D.; Kumar A.; Bedi P.; Athavale V.A.; Veeraiah D.; Pratap B.R.
- Description
- As of late, the Internet of Things (IoT) innovation has been utilized in applications, for example, transportation, medical care, video observation, and so on. The quick appropriation and development of IoT in these segments are producing an enormous measure of information. For instance, IoT gadgets, for example, cameras produce various pictures when utilized in medical clinic reconnaissance sees. Here, face acknowledgement is one of the most significant instruments that can be utilized for clinic affirmations, enthusiastic discovery, and identification of patients, location of fake gadgets. patient, and test clinic models. Programmed and shrewd face acknowledgement frameworks are profoundly precise in an overseen climate; notwithstanding, they are less exact in an unmanaged climate. Additionally, frameworks must keep on running on numerous occasions in different applications, for example, insightful wellbeing. This work presents a tree-based profound framework for programmed face acknowledgement in a cloud climate. The inside and out pattern have been proposed to cost less for the PC without focusing on unwavering quality. In the model, the additional size is isolated into a few sections, and a stick is made for each part. The tree is characterized by its branch area and stature. The branches are spoken to by a leftover capacity, which comprises of a twofold layer, a stack game plan, and a non-direct capacity. The proposed technique is assessed in an assortment of generally accessible information bases. An examination of the method is likewise finished with top to bottom craftsmanship models for the eye to eye connection. The aftereffects of the tests indicated that the example was considered to have accomplished a precision of 98.65%, 99.19%, and 95.84%. 2020
- Source
- Microprocessors and Microsystems, Vol-81
- Date
- 2021-01-01
- Publisher
- Elsevier B.V.
- Subject
- Cloud; Deep learning; Deep neural network; Edge computing; IoT
- Coverage
- Chauhan D., Department of Computer Science & Engineering, Shivajirao Kadam Institute of Technology & Management, Indore, Madhya Pradesh, India; Kumar A., Assistant Professor &Director (Hon.), P.G. Department Of Law, Centre for Cyber Law and Policy Research, SRNCT, Faculty of Legal Studies, M.J.P. Rohilkhand University, Bareilly, Uttar Pradesh, India; Bedi P., Associate Professor, Department of Computer Science and Engineering, Graphic Era Hill University, Dehradun, Uttarakhand, India; Athavale V.A., Department of Computer Science and Engineering, Panipat Institute of Engineering & Technology, Panipat, Haryana, India; Veeraiah D., Department of Computer Science and Engineering, Lakireddy Bali Reddy College of Engineering (A), Mylavaram, Krishna Dt., Andhra Pradesh, India; Pratap B.R., Department of Computer Science & Engineering, CHRIST (Deemed to be University), Bengaluru, Karnataka, India
- Rights
- Restricted Access
- Relation
- ISSN: 1419331; CODEN: MIMID
- Format
- Online
- Language
- English
- Type
- Article
Collection
Citation
Chauhan D.; Kumar A.; Bedi P.; Athavale V.A.; Veeraiah D.; Pratap B.R., “An effective face recognition system based on Cloud based IoT with a deep learning model,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/15885.