• Land cover mapping of mixed classes using 2D CNN with multi-frequency SAR data 

  Phartiyal, Gopal Singh (Elsevier, 2024-07)

  Synthetic aperture radar (SAR) data obtained at multiple frequencies and polarizations offers valuable complementary information for classifying mixed classes that exhibit similar backscattering response. Although deep ...
• Fractional crop cover estimation via drone imagery and machine learning with color models 

  Phartiyal, Gopal Singh (IEEE, 2024)

  Drones have become increasingly popular in precision agriculture due to their ability to collect valuable data quickly and efficiently. One of the major aspects of precision agriculture is to estimate fraction crop cover ...
• Improved mapping of flood affected villages in India: a novel three-stage approach using PolSAR polarization signatures and ensembled dilated CNNs 

  Phartiyal, Gopal Singh (Taylor & Francis, 2023-11)

  During floods, updated and accurate information on affected human settlements helps save lives and reduces time to rescue. Therefore, approaches that can provide reliable information during floods via the use of all-weather ...
• Synthetic imaging radar data generation in various clutter environments using novel uwb log-periodic antenna 

  Phartiyal, Gopal Singh (MDPI, 2024-12)

  In short-range microwave imaging, the collection of data in real environments for the purpose of developing techniques for target detection is very cumbersome. Simultaneously, to develop effective and efficient AI/ML-based ...
• An unconstrained primal based twin parametric insensitive support vector regression 

  Richhariya, Bharat (World Scientific, 2025)

  In this paper, we propose an efficient regression algorithm based on primal formulation of twin support vector machine. This is an efficient approach to solve the optimization problem leading to reduced computation time. ...
• System test case design from requirements specifications: insights and challenges of using chatgpt 

  Kumar, Dhruv (2024)

  System testing is essential in any software development project to ensure that the final products meet the requirements. Creating comprehensive test cases for system testing from requirements is often challenging and ...
• Debatebench: a challenging long context reasoning benchmark for large language models 

  Kumar, Dhruv (2025-02)

  We introduce DebateBench, a novel dataset consisting of an extensive collection of transcripts and metadata from some of the world's most prestigious competitive debates. The dataset consists of British Parliamentary debates ...
• Analyzing LLM usage in an advanced computing class in india 

  Kumar, Dhruv (ACM Digital Library, 2025-04)

  This study examines the use of large language models (LLMs) by undergraduate and graduate students for programming assignments in advanced computing classes. Unlike existing research, which primarily focuses on introductory ...
• Revieweval: an evaluation framework for ai-generated reviews 

  Kumar, Dhruv (2025)

  The escalating volume of academic research, coupled with a shortage of qualified reviewers, necessitates innovative approaches to peer review. While large language model (LLMs) offer potential for automating this process, ...
• DTA-HMR-TT: dynamic task allocation for a heterogeneous team of mobile robots with task transfer 

  Gautam, Avinash; Shekhawat, Virendra Singh; Mohan, Sudeept (IEEE, 2024-11)

  Managing time-sensitive deliveries in settings like hospitals is a challenging task, especially when multiple pickup and delivery requests need to be coordinated efficiently within strict time windows. This paper focuses ...
• An attention-based deep network for plant disease classification 

  Bera, Asish (2024)

  Plant disease classification using machine learning in a real agricultural field environment is a difficult task. Often, an automated plant disease diagnosis method might fail to capture and interpret discriminatory ...
• Poa-net: dance poses and activity classification using convolutional neural networks 

  Bera, Asish (IEEE, 2024)

  Dance poses represent a complex human body-part movement, and express emotions and gesture. Dance pose classification is a challenging problem in computer vision. Convolutional Neural Networks (CNNs) have witnessed significant ...
• RAFA-net: region attention network for food items and agricultural stress recognition 

  Bera, Asish (IEEE, 2024-10)

  Deep convolutional neural networks (CNNs) have facilitated remarkable success in recognizing various food items and agricultural stress. A decent performance boost has been witnessed in solving the agro-food challenges by ...
• Fluorescence microscopy and histopathology image based cancer classification using graph convolutional network with channel splitting 

  Bera, Asish (Elsevier, 2025-05)

  Since the proliferation of deep learning, several convolutional neural networks (CNNs) are developed to attain significant breakthroughs for automated cancer classification using histopathology and fluorescence microscopy ...
• Privacy-preserving password-based authentication using zero-knowledge proofs 

  Bhatia, Ashutosh; Tiwari, Kamlesh (IEEE, 2025-03)

  Passwords remain fundamental to user authentication, including handheld devices, wearables, personal computers, and network devices. Privacy concerns have led to the development of new password guidelines and alternatives, ...
• Quantum key distribution optimization: reducing communication overhead in post-processing steps 

  Bhatia, Ashutosh; Bitragunta, Sainath; Tiwari, Kamlesh (IEEE, 2025-03)

  Quantum Key Distribution (QKD) is a ground-breaking method in modern cryptography that uses quantum mechanics to establish secure communication channels. Unlike classical cryptographic techniques, QKD provides unconditional ...
• Efficient routing for QKD network using novel quantum optimization approach 

  Bitragunta, Sainath; Bhatia, Ashuthosh (IEEE, 2025)

  With exponential growth and associated milestones set in quantum information and quantum computing (QC) technologies, QC is becoming a threat to existing key encryption strategies that leverage asymmetric cryptographic ...
• Enhanced lightweight quantum key distribution protocol for improved efficiency and security 

  Bhatia, Ashutosh; Bitragunta, Sainath; Tiwari, Kamlesh (IEEE, 2025)

  Quantum Key Distribution (QKD) provides secure communication by leveraging quantum mechanics, with the BB84 protocol being one of its most widely adopted implementations. However, the classical post-processing steps in ...
• Quantum computing-accelerated kalman filtering for satellite clusters: algorithms and comparative analysis 

  Bitragunta, Sainath; Bhatia, Ashutosh; Tiwari, Kamlesh (IEEE, 2025-01)

  The increasing demand for high-precision real-time data processing in satellite clusters requires efficient algorithms to manage inherent uncertainties in space-based systems. We propose an innovative framework that ...
• Secrecy capacity and efficiency outage analysis of cooperative phy-secure wireless systems and secrecy capacity-based RIS design 

  Bitragunta, Sainath; Bhatia, Ashutosh (IEEE, 2025-03)

  Physical layer (PHY) security (PLS) leverages the inherent randomness of wireless fading channels to provide enhanced secrecy capacity. In this work, we consider a four-node, dual hop, eavesdropper-aware cooperative ...

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