Pathmanaban Pugazhendi
Also known as: Pathmanaban Pugazhendi, P.Pathmanaban, Pugazhendi Pathmanaban
Research areas: Computer Science · Computer Vision and Pattern Recognition · Advanced Neural Network Applications · Smart Agriculture and AI · Industrial Vision Systems and Defect Detection
0000-0002-0371-2586
About
Dr. P. Pathmanaban is an accomplished academician and researcher specializing in the domains of computer vision, thermal image processing, and deep learning applications in engineering and agriculture. He currently serves as an Assistant Professor in the Department of Automobile Engineering at Easwari Engineering College, Chennai. With over 11 years of academic experience, Dr. Pathmanaban has made significant contributions in AI-based fruit defect detection, electric vehicle battery management, and smart composite materials. His interdisciplinary research has been published in prestigious international journals including Elsevier, Springer, Wiley, Taylor & Francis, and IEEE Xplore.
Area of Research Interest :
Deep Learning and Computer Vision, Thermal Image Processing for Safety and Agriculture, Smart Composite Materials and Bio-Composites, Battery Management Systems in Electric Vehicles, AI Applications in Smart Agriculture and Post-Harvest Quality, Infrared and Non-Destructive Testing Techniques
Employment
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Education
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Publications (43)
- Experimental and machine-learning based investigation of second generation juliflora biodiesel blended with dimethyl carbonate and CoCr 2 O 4 nanoparticles in a compression ignition engine Save
- Infrared thermography for defect detection in fiber-reinforced polymer composites: A physics-informed analytical synthesis and review Save
- Data-driven robust design for industrial cylindrical plunge grinding of piston rings: Requirements for reliable digital-twin development under production noise Save
- Hydrogen enriched biodiesel with a CuO‐WO3‐g‐C3N4 nanocomposite for enhanced performance and emission reduction in a CI engine using experimental and machine learning approaches Save
- Machine learning-based fault detection in low-speed bearings using a multi-environmental dataset Save
- Transient Thermal Response of Banana–Bagasse Fiber Hybrid Biocomposite Plates with Conch Shell Filler Using Active Infrared Thermography Save
- Distance-dependent thermal response of Nano-modified Aluminium-GFRP fiber metal laminates: A comparative experimental study Save
- Advances in agricultural fruit detection using you only look once (YOLO) algorithm: A review Save
- Digitized visual measurement system using MobileNetV2-CBAM for automated sapota quality grading Save
- Uncertainty-Aware Deep Learning for Sugarcane Leaf Disease Detection Using Monte Carlo Dropout and MobileNetV3 Save
- Areca–Glass Fiber Hybrid Sandwich Composites: Location-Dependent Transient Thermal Behavior of a Bio-Derived Hybrid Material System Save
- Benchmarking YOLO nano-architectures for real-time thermal imaging: application to okra maturity grading on heterogeneous computing platforms Save
- Comprehensive Benchmarking of YOLO Architectures for Real-Time Agricultural Object Detection: A Case Study in Citrus Fruit Recognition Save
- Grid seasonality, vehicle efficiency and battery electric vehicle emissions across 209 countries Save
- Lightweight deep learning models for visual weld defect inspection: balancing speed and accuracy with YOLO architectures Save
- Location-dependent transient surface-temperature response of areca–glass fiber hybrid sandwich composites under localized heating using infrared thermography Save
- Train–Test Leakage in Pothole Detection Benchmarks: Evidence from a Video-Disjoint Re-Split of BharatPotHole Save
- Experimental and machine learning based investigation of performance and emission characteristics of a CI engine using fusel oil blends Save
- YOLOv11n for precision agriculture: lightweight and efficient detection of guava defects across diverse conditions Save
- Predicting Color Development and Texture Changes in Tomatoes Treated With Hot Water and Exposed to High‐Temperature Ethylene Using Support Vector Regression Save