Praveen M Naik

About

Praveen M Naik was born in Karnataka, India,in 1987. He received the BE degree in Information Science and Engineering and the M.Tech. degree in Computer Science and Engineering from the Visvesvaraya Technological University, Belagavi,Karnataka, India in 2010 and 2013, respectively. He was teaching with the Department of Computer Science and Engineering, Visvesvaraya Technological University, Belagavi,Karnataka, India till 2020. Currently he is working as Ph.D. scholar in National Institute of Technology Karnataka, Suratkal, India.His research interests are Image Processing, IoT, Blockchain, Machine Learning.

Employment

• Nitte University Assistant Professor Grade III
  2024 - Present
• Shri Madhwa Vadiraja Institute of Technology & Management Assistant Professor
  2013 - 2020

Education

• National Institute of Technology Karnataka Ph.D. Pursuing
  2020 - Present
• Atria Institute of Technology Master of Technology
  2011 - 2013
• NMAM Institute of Technology Bachelor of Engineering
  2006 - 2010

Projects & Funding

Projects & funding information is unavailable.

Publications (11)

• CurveGuard: An Intelligent System for Preventing Accidents on Road Curves
  2025 International Conference on Intelligent Systems and Pioneering Innovations in Robotics and Electric Mobility (INSPIRE) 2025 DOI: 10.1109/inspire67328.2025.11300613
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• Analyzing the Effect of Text Vectorization and Word2vec on Bayesian Optimization for Mental Health Text Classification Using Deep Learning
  2025 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER) 2025 DOI: 10.1109/discover66922.2025.11258971
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• Comparative Analysis of Deep Learning Models for Forecasting NIFTY50 and NIFTY500 Indices using Technical Indicators
  2025 Global Conference on Information Technology and Communication Networks (GITCON) 2025 DOI: 10.1109/gitcon65266.2025.11376837
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• X-ArecaNet: Dataset of arecanut X-ray images for deep learning applications
  Data in Brief 2025 DOI: 10.1016/j.dib.2025.111721
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• Quantum‐inspired Arecanut X‐ray image classification using transfer learning
  IET Quantum Communication 2024 DOI: 10.1049/qtc2.12099
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• Framework for Lightweight Deep Learning Model Using YOLOv5 for Arecanut Grade Assessment
  SN Computer Science 2024 DOI: 10.1007/s42979-024-03384-1
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• Optimizing Object Detection in YOLOv5 using Adaptive Genetic Algorithm: A Study on Population Sizes for Enhanced Accuracy
  2024 3rd International Conference for Innovation in Technology (INOCON) 2024 DOI: 10.1109/inocon60754.2024.10512119
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• Deep learning-based arecanut detection for X-ray radiography: improving performance and efficiency for automated classification and quality control
  Nondestructive Testing and Evaluation 2024 DOI: 10.1080/10589759.2024.2327000
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• Classification of Arecanut X-Ray Images for Quality Assessment Using Adaptive Genetic Algorithm and Deep Learning
  IEEE Access 2023 DOI: 10.1109/ACCESS.2023.3332215
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• Flower Phenotype Recognition and Analysis using YoloV5 Models
  13th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2022 2022
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