RINKU DATTA RAKSHIT

About

Rinku Datta Rakshit, presently working as an Associate professor at the School of Computer Engineering, Kalinga Institute of Industrial Technology, deemed to be University, Bhubaneswar, Odisha. She completed her B.Tech (Information Technology) in 2005 from Jalpaiguri Government Engineering College, Jalpaiguri, West Bengal. She completed her M.Tech (Multimedia & Software Systems) in 2011 from National Institute of Technical Teachers’ Training & Research, Kolkata. She did her Ph.D (Computer Science and Engineering) in 2021 from National Institute of Technology Durgapur. She received Visvesvaraya fellowship for completion of her PhD under “Visvesvaraya PhD Scheme for Electronic & IT”, Ministry of Electronics and Information Technology, Government of India. She has more than 16 years of teaching experience. She is a Wipro Certified faculty. She worked as an organizing committee member, reviewer, and session chair in some international conferences. Her research area includes image processing, biometrics, and machine learning. Her publications include many SCI indexed journals, conferences and book chapters.

Employment

• KIIT Deemed to be University Associate Professor
  2023 - Present

Education

Education history is unavailable.

Projects & Funding

Projects & funding information is unavailable.

Publications (11)

• Biometric-based computer vision for boundless possibilities: process, techniques, and challenges
  Intelligent Multimedia Processing and Computer Vision: Techniques and applications 2023 DOI: 10.1049/pbpc064e_ch3
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• Machine learning and revolution in agriculture: past, present and future
  Intelligent Multimedia Processing and Computer Vision: Techniques and applications 2023 DOI: 10.1049/pbpc064e_ch11
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• An LDOP approach for face identification under unconstrained scenarios
  Journal of Experimental & Theoretical Artificial Intelligence 2023 DOI: 10.1080/0952813x.2023.2183274
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• Iris Recognition Using Symmetric Graph Structure Based Pattern Matching
  Communications in Computer and Information Science 2022 DOI: 10.1007/978-3-031-15556-7_1
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• Cross-resolution face identification using deep-convolutional neural network
  Multimedia Tools and Applications 2021 DOI: 10.1007/s11042-021-10745-y
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• Face Identification via Strategic Combination of Local Features
  Computational Intelligence in Pattern Recognition 2020 DOI: 10.1007/978-981-13-9042-5_18
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• Biometric Technologies in Healthcare Biometrics
  Advances in Medical Technologies and Clinical Practice 2019 DOI: 10.4018/978-1-5225-7525-2.ch001
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• Face Identification Using Local Ternary Tree Pattern Based Spatial Structural Components
  Pattern Recognition and Image Analysis 2019 DOI: 10.1007/978-3-030-31321-0_5
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• Face identification using some novel local descriptors under the influence of facial complexities
  Expert Systems with Applications 2018 DOI: 10.1016/j.eswa.2017.09.038
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• An improved local pattern descriptor for biometrics face encoding: a LC–LBP approach toward face identification
  Journal of the Chinese Institute of Engineers 2017 DOI: 10.1080/02533839.2016.1259020
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