Vinod Chandran

About

Vinod Chandran was a Professor at QUT and conducted research in signal processing, image processing, computer vision and machine learning with applications to bio-metric and biomedical systems.

Employment

Employment history is unavailable.

Education

• Washington State University Master of Science (Computer Science)
  ? - 1991
• Washington State University PhD
  ? - 1990
• Texas Tech University Master of Science (Electrical Engineering)
  ? - 1985
• Indian Institute of Technology Madras B. Tech. Electrical Engineering (Electronics)
  ? - 1982

Projects & Funding

Projects & funding information is unavailable.

Publications (109)

• HOS-FingerCode: Bispectral invariants based contactless multi-finger recognition system using ridge orientation and feature fusion
  Expert Systems with Applications 2022 DOI: 10.1016/j.eswa.2022.117054
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• Segmentation of White Blood Cell, Nucleus and Cytoplasm in Digital Haematology Microscope Images: A Review–Challenges, Current and Future Potential Techniques
  IEEE Reviews in Biomedical Engineering 2021 DOI: 10.1109/RBME.2020.3004639
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• 3D Face Tracking Using Stereo Cameras: A Review
  IEEE Access 2020 DOI: 10.1109/ACCESS.2020.2994283
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• Automatic Emotion Recognition Using Temporal Multimodal Deep Learning
  IEEE Access 2020 DOI: 10.1109/ACCESS.2020.3027026
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• Prediction of Relative Physical Activity Intensity Using Multimodal Sensing of Physiological Data
  Sensors 2019 DOI: 10.3390/s19204509
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• Combining multi-channel color space with local binary co-occurrence feature descriptors for accurate smoke detection from surveillance videos
  Fire Safety Journal 2018 DOI: 10.1016/j.firesaf.2018.09.003
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• Part based bit error analysis of iris codes
  Pattern Recognition 2016 DOI: 10.1016/j.patcog.2016.05.022
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• Representation of facial expression categories in continuous arousal–valence space: Feature and correlation
  Image and Vision Computing 2014 DOI: 10.1016/j.imavis.2014.09.005
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• Breast cancer detection from thermal images using bispectral invariant features
  2013 DOI: 10.1016/j.ijthermalsci.2013.03.001
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• Evaluation of image resolution and super-resolution on face recognition performance
  2012 DOI: 10.1016/j.jvcir.2011.06.004
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