Enhanced Security in Payment Gateways Through Face Detection: An Advanced Approach Using DenseNet 121- BiLSTM Models
- Title
- Enhanced Security in Payment Gateways Through Face Detection: An Advanced Approach Using DenseNet 121- BiLSTM Models
- Creator
- Gowsic K.; Sowmiya M.; Nirmala Devi M.; Chauhan A.; Arul Mary Rexy V.; Singh D.
- Description
- Because it is one of the most promising applications of image analysis, face recognition has been the subject of intense research and development for many decades. Many modern identification and verification requirements have found a potential new home with the introduction of face recognition (FR) technology. Facial recognition is just one of numerous uses for biometric pattern recognition algorithms. Sequencing is essential for many tasks, including as feature extraction, model training, and preprocessing. Eliminating background noise and obtaining dense vertical edges are part of the preprocessing procedures. Facial feature extraction will be employed to extract features after feature extraction. Use attributes cautiously when training a Desnet121-BiLSTM model. In every respect, the suggested method outperforms two state-of-the-art algorithms, Desnet121 and BiLSTM. An accuracy rating of 97.19% was indicative of a considerable improvement in the figures. 2024 IEEE.
- Source
- 1st International Conference on Electronics, Computing, Communication and Control Technology, ICECCC 2024
- Date
- 2024-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- Facial Recognition (FR); Field Programmable Gate Arrays (FPGA); Payment System
- Coverage
- Gowsic K., Mahendra Engineering College (Autonomous), Department of Computer Science and Engineering, Namakkal, India; Sowmiya M., Mahendra Engineering College (Autonomous), Department of Computer Science and Engineering, Namakkal, India; Nirmala Devi M., School of Sciences, CHRIST (Deemed to be University), Department of Life Sciences, Karnataka, Bengaluru, India; Chauhan A., St. Martin's Engineering College, Department of English, Secunderabad, India; Arul Mary Rexy V., Saveetha College of Liberal Arts and Sciences, SIMATS, Department of Commerce, Kuthambakkam, India; Singh D., School of Management Sciences, Department of Applied Science, Lucknow, India
- Rights
- Restricted Access
- Relation
- ISBN: 979-835037180-2
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Gowsic K.; Sowmiya M.; Nirmala Devi M.; Chauhan A.; Arul Mary Rexy V.; Singh D., “Enhanced Security in Payment Gateways Through Face Detection: An Advanced Approach Using DenseNet 121- BiLSTM Models,” CHRIST (Deemed To Be University) Institutional Repository, accessed April 25, 2025, https://archives.christuniversity.in/items/show/19289.