VINOD KUMAR

About

I am currently working as an Assistant Professor at the School of Computer Science, UPES, Dehradun. Prior to this, I completed my PhD in Computer Science and Engineering from IIT (BHU) Varanasi, where I specialized in computer vision and deep learning. My PhD research focuses on hyperspectral image classification, aiming to advance spectral-spatial feature extraction techniques for enhanced classification performance. I pursued my PhD under the supervision of Prof. Ravi Shankar Singh.

Employment

• UPES Assistant Professor
  2025 - Present
• KPIT Technologies Software Engineer
  2017 - 2018

Education

• Indian Institute of Technology BHU Ph.D.
  2018 - 2025
• Indian Institute of Technology Kharagpur M.Tech
  2015 - 2017
• Indian Institute of Technology BHU B.Tech
  2010 - 2014

Projects & Funding

Projects & funding information is unavailable.

Publications (14)

• Lightweight Logarithmic Group Convolution Network with Polarized Attention for Hyperspectral Image Classification
  Computer Vision and Image Processing 2026
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• Demystifying SAR with attention
  Expert Systems with Applications 2025 DOI: 10.1016/j.eswa.2025.127182
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• Enhancing Hyperspectral image classification through transformer-based contextualization and novel logarithmic convolutional techniques
  Infrared Physics & Technology 2025 DOI: 10.1016/j.infrared.2025.105826
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• Deep learning for hyperspectral image classification: A survey
  Computer Science Review 2024 DOI: 10.1016/j.cosrev.2024.100658
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• CKGFLNet: A Fast Hybrid Architecture for Hyperspectral Image Classification Leveraging Kaiming-Gaussian Attention
  International Conference on Machine Learning, Image Processing, Network Security and Data Sciences 2024
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• CKGFLNet: A Fast Hybrid Architecture for Hyperspectral Image Classification Leveraging Kaiming-Gaussian Attention
  International Conference on Machine Learning, Image Processing, Network Security and Data Sciences 2024
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• Efficient task scheduling on the cloud using artificial neural network and particle swarm optimization
  Concurrency and Computation: Practice and Experience 2024 DOI: 10.1002/cpe.7954
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• Morphologically dilated convolutional neural network for hyperspectral image classification
  Signal Processing: Image Communication 2022 DOI: 10.1016/j.image.2021.116549
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• Compression of multi-temporal hyperspectral images based on RLS filter
  Visual Computer 2022 DOI: 10.1007/s00371-020-02000-6
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• Frequency Domain Based Convolutional Neural Network for Land Cover Classification
  2022 DOI: 10.2139/ssrn.4220758
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