Prabhu Prasad Dev
Verified @gmail.com
Scopus Publications
- Cross-modal uncertainty modeling framework for unseen video anomaly detection
Prabhu Prasad Dev, Pranesh Das, Raju Hazari
Neurocomputing, 2026 - Detecting AI-generated essays using fine-tuned XLNet-CNN hybrid techniques: a study of the academic integrity challenge
Manish Prajapati, Santos Kumar Baliarsingh, Prabhu Prasad Dev
International Journal of Machine Learning and Cybernetics, 2026 - Detecting AI-generated text in high-resource languages: developing a RoBERTa-CNN hybrid model for academic integrity challenge
Manish Prajapati, Santos Kumar Baliarsingh, Prabhu Prasad Dev
International Journal of Machine Learning and Cybernetics, 2026 - Testing Privacy-Preserving AI-Generated Text Detection Using Large Language Models
Manish Prajapati, Santos Kumar Baliarsingh, Jasaswi Prasad Mohanty, Prabhu Prasad Dev, Jhalak Hota, Manas Ranjan Biswal
Esic 2026 Proceedings 6th International Conference on Emerging Systems and Intelligent Computing, 2026
With the rise of large language models (LLMs), students are increasingly relying on AI systems for academic writing. While these tools can aid learning, they also compromise educational integrity by facilitating plagiarism and hindering skill development. Current AI-detection systems primarily depend on cloud-based APIs, raising serious privacy concerns as sensitive student data must be uploaded to third-party servers. This research proposes a privacy-preserving detection framework that enables on-device and federated AI-detection models enhanced with differential privacy (DP). Our framework integrates lightweight Transformer architectures, quantization for mobile deployment, and federated aggregation, allowing institutions to detect AI-generated text without exposing private data. We present the mathematical intuition of our proposed model, design experiments comparing human vs. AI-authored essays, and demonstrate deployment of quantized models using TensorFlow Lite. Results indicate that our framework achieves <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{9 4 \%}$</tex> detection accuracy on mobile devices while ensuring data privacy. This research highlights the feasibility of decentralized AI-detection systems in education, addressing both academic integrity and ethical privacy considerations. - A modified Gray Wolf Optimization algorithm for early detection of Parkinson's Disease
Krishnapriya Santhosh, Prabhu Prasad Dev, Binu Jose A., Zorana Lynton, Pranesh Das, Ebrahim Ghaderpour
Biomedical Signal Processing and Control, 2025
Parkinson’s disease (PD) is one of the most common neurodegenerative diseases, causing significant morbidity and mortality worldwide. PD can be diagnosed at an early stage by analyzing patient datasets, such as speech and handwriting samples. In this paper, a modified version of the classical Gray Wolf Optimization (GWO) is proposed with an application to detect early-stage PD through processing such datasets. The new model (MGWO-eP) aims to enhance the algorithm’s exploration capability (e) and overcome local optima issues by adjusting a key parameter (P) that controls the search agents’ positions. The MGWO-eP is then applied as a feature selection technique to predict PD in its early stages, using samples of speech and writing. The effectiveness of MGWO-eP is validated by benchmark optimization functions for achieving the global optimum. Then six popular machine learning classifiers are applied to three benchmark PD prediction datasets that include hand-writing and speech samples from people with and without PD, namely HandPD Spiral, HandPD Meander, and SpeechPD. The proposed model achieves best overall accuracies of 96.30% (with voting), 94.45% (with random forest), and 98.31% (with voting), outperforming GWO and particle swarm optimization algorithms as they get stuck with local optimal solutions. The results show that the proposed model is robust and can be used for early detection of PD in patients through analyzing datasets, such as their handwriting and speech to help the patients access treatments early in the disease, prolonging time spent with adequate symptom control and delaying years of disability/morbidity. • A modified gray wolf optimization algorithm is proposed, namely MGWO-eP. • The MGWO-eP is successfully applied to detect early-stage Parkinson’s disease. • The MGWO-eP is validated by benchmark optimization functions for achieving the global optimum. • Three benchmark Parkinson’s Disease (PD) prediction datasets are utilized. - CA-VAD: Caption Aware Video Anomaly Detection in surveillance videos
Debi Prasad Senapati, Santosh Kumar Pani, Santos Kumar Baliarsingh, Prabhu Prasad Dev, Hrudaya Kumar Tripathy
Journal of Visual Communication and Image Representation, 2025 - Dynamic Time Slice Prediction in Round Robin CPU Scheduling using Machine Learning
Bismaya Kanta Dash, Prabhu Prasad Dev, Santosh Kumar Pani
Esic 2025 5th International Conference on Emerging Systems and Intelligent Computing Proceedings, 2025
Efficient CPU scheduling is crucial for optimizing system performance and resource utilization in multitasking operating systems. The Round Robin (RR) scheduling algorithm, known for its simplicity and fairness, often suffers from inefficiencies due to its use of a constant time slice, leading to increased waiting time (WT) and turnaround time (TAT) under varying workloads. This research addresses these limitations by proposing an optimized RR CPU scheduling algorithm that employs dynamic time slicing (DTS) using Artificial Neural Networks (ANN). DTS is adjusted based on CPU burst time (BT), with the aim of minimizing WT and TAT. Various regression techniques and ANN models are utilized to predict the DTS. These models are trained and evaluated using GWA-T-4 AuverGrid dataset of process attributes, with key performance metrics such as Mean Squared Error (MSE), R-squared (R2), average WT and average TAT used to assess their effectiveness. Experimental results demonstrate that the proposed RR method, especially when optimized with ANN, significantly reduces WT and TAT compared to other RR methods. - MCANet: Multimodal Caption Aware Training-Free Video Anomaly Detection via Large Language Model
Prabhu Prasad Dev, Raju Hazari, Pranesh Das
Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2025 - Real-Time Pose Estimation Using Lightweight High Resolution Network
Subhash Kumar, Prabhu Prasad Dev, Jasaswi Prasad Mohanty, Santos Kumar Baliarsingh, Jhalak Hota
Ocit 2025 Proceedings 23rd Oits International Conference on Information Technology, 2025
Human pose estimation is a fundamental problem in computer vision and has been widely used in various fields such as medical applications, virtual reality, and the sports sector. In this paper, we propose a hybrid deep neural network architecture that merges the light-weighted efficacy of Lite-HRNet with the multi-resolution and context modeling flair of HRViT. By integrating Conditional Channel Weighting (CCW), cross-resolution fusion, and self-attention, we effectively optimize both accuracy and speed of our proposed method. Our method achieves an AP@50 of 88.6 % and an mAP of 75.3 % on the COCO dataset, with only 1.8 million parameters and an inference time of 13 ms per image. Comparable strong results are also observed on the MPII and PoseTrack datasets. Both qualitative and quantitative evaluations confirm the robustness of our approach across challenging scenarios such as occlusions, low-resolution inputs, and multi-person interactions. Moreover, it demonstrates that the model performs superior performance in real-time scenarios with limited resources. Future research will be dedicated to investigating 3D pose prediction as well as the process of making it more efficient on the edge device. - MSPL-VAD: Multi-Stage Pseudo-Labeling framework for Video Anomaly Detection
Debi Prasad Senapati, Santosh Kumar Pani, Santos Kumar Baliarsingh, Manas Ranjan Nayak, Prabhu Prasad Dev
International Conference on Innovations in Intelligent Systems Advancements in Computing Communication and Cybersecurity Isac3 2025, 2025
Video anomaly detection is challenging due to the rare occurrence, high variability, and difficulty in defining anomalies. Traditional methods rely on manual annotations, struggle with generalization, and are computationally expensive. To address the aforementioned issues, we propose a Multi-Stage Pseudo-Labeling framework for Video Anomaly Detection (MSPL-VAD). Our framework integrates Global Pseudo-Labeling (GPL) with Deep Embedded Clustering for coarse separation of normal and anomalous instances, followed by Local Pseudo-Labeling (LPL) using Kernel Density Estimation to refine segment-level labels with greater precision. Furthermore, we also introduce a self-attention-based anomaly detector that can be effectively applied to segments of an unseen test video, producing anomaly predictions at both the segment and frame levels. To validate the effectiveness of the proposed MSPL-VAD, we have conducted experiments on UCSD Ped2, CUHK Avenue, ShanghaiTech, and UCF-Crime. Experimental results demonstrate that our approach achieves superior performance than state-of-the-art results. - Detecting AI-Generated Text Using Fine-Tuned Transformers: A Study on Academic Integrity
Manish Prajapati, Santos Kumar Baliarsingh, Prabhu Prasad Dev, Bashir Maina Saleh, Jhalak Hota, Manas Ranjan Biswal
Communications in Computer and Information Science, 2025 - Multi-Attribute AI-based Storytelling Framework with IoT Deployment for Real-Time Narration: A Parameter-Efficient Approach
Sankalp Nayak, Samriddhi Sharma, Aradhana Behura, Prabhu Prasad Dev, Jitendra Kumar Rout, Madhukrishna Priyadarsini
Ised 2025 13th International Conference on Intelligent Systems and Embedded Design Proceedings, 2025 - Weakly Supervised Temporal Attention Framework for Video Anomaly Detection
Manas Ranjan Biswal, Prabhu Prasad Dev, Santos Kumar Baliarsingh
2024 15th International Conference on Computing Communication and Networking Technologies Icccnt 2024, 2024 - ReFLIP-VAD: Towards Weakly Supervised Video Anomaly Detection via Vision-Language Model
Prabhu Prasad Dev, Raju Hazari, Pranesh Das
IEEE Transactions on Circuits and Systems for Video Technology, 2024 - Single-Cell Drug Perturbations Prediction Using Machine Learning
Manish Prajapati, Santos Kumar Baliarsingh, Prabhu Prasad Dev, Sankalp Nayak, Manas Ranjan Biswal
Communications in Computer and Information Science, 2024 - Temporal Relation-Embedded Transformer for Weakly-Supervised Video Anomaly Detection
Tonmoyee Chowdhury, Prabhu Prasad Dev, Santos Kumar Baliarsingh, Jasaswi Prasad Mohanty, Manas Ranjan Biswal
Proceedings 11th International Conference on Signal Processing and Integrated Networks Spin 2024, 2024 - Detection and Classification of Blood Cancer Using Deep Learning Framework
Manish Prajapati, Santos Kumar Baliarsingh, Jhalak Hota, Prabhu Prasad Dev, Shuvam Das
Lecture Notes in Electrical Engineering, 2024 - CFViT: Coarse and Fine-grained Vision Transformer for Vehicle Re-Identification
Shrishti Priya Sinha, Prabhu Prasad Dev, Santos Kumar Baliarsingh, Raj Aryan Behera, Jasaswi Prasad Mohanty
Proceedings 2024 Oits International Conference on Information Technology Ocit 2024, 2024 - DG-GAN: A Deep Neural Network for Real-World Anomaly Detection in Surveillance Videos
Debi Prasad Senapati, Prabhu Prasad Dev, Santos Kumar Baliarsingh, Sankalp Nayak, Manas Ranjan Biswal
Communications in Computer and Information Science, 2024 - STFANet: Learning spatio-temporal feature aggregation for person re-identification
Raj Aryan Behera, Prabhu Prasad Dev, Santos Kumar Baliarsingh, Shrishti Priya Sinha, Manas Ranjan Biswal
Proceedings 2024 Oits International Conference on Information Technology Ocit 2024, 2024 - A Smartphone-based Deep Learning Framework for Early Detection of Oral Cancer Signs
Santos Kumar Baliarsingh, Prabhu Prasad Dev, Anjan Bandyopadhyay, Amiya Kumar Dash, Roshni Pradhan
Esic 2024 4th International Conference on Emerging Systems and Intelligent Computing Proceedings, 2024 - Brain Tumour Classification: A Comparative Analysis of CNN Models and Generalisation Across Datasets
Aheli Manna, Aditya Saha, Jahnvi Jain, Aditya Kamal, Santos Kumar Baliarsingh, Prabhu Prasad Dev
Proceedings 2024 Oits International Conference on Information Technology Ocit 2024, 2024 - An Early diagnosis of diabetic retinopathy using ConvNeXt
Devanshi, Santos Kumar Baliarsingh, Prabhu Prasad Dev
Proceedings of the 10th International Conference on Signal Processing and Integrated Networks Spin 2023, 2023 - MSDeepNet: A Novel Multi-stream Deep Neural Network for Real-World Anomaly Detection in Surveillance Videos
Prabhu Prasad Dev, Pranesh Das, Raju Hazari
Communications in Computer and Information Science, 2023 - Dynamic Population-Based Jaya Algorithm for Genetic Biomarker Classification
Santos Kumar Baliarsingh, Prabhu Prasad Dev, Ashutosh Bhoi, Jasaswi Prasad Mohanty, Jhalak Hota
Ocit 2023 21st International Conference on Information Technology Proceedings, 2023 - IoT-Based Smart Irrigation System for Optimal Water-Resource Utilization in Indian Agriculture
Ashutosh Bhoi, Santos Kumar Baliarsingh, Prabhu Prasad Dev, Umashankar Ghugar, Manas Ranjan Biswal
Ocit 2023 21st International Conference on Information Technology Proceedings, 2023 - Retinal and Semantic Segmentation of Diabetic Retinopathy Images Using MobileNetV3
Manish Prajapati, Santos Kumar Baliarsingh, Jhalak Hota, Prabhu Prasad Dev, Shuvam Das
Iccece 2023 International Conference on Computer Electrical and Communication Engineering, 2023 - CNNViT: A robust deep neural network for video anomaly detection
N. Garuda, G. Prasad, P. P. Dev, P. Das, E. Ghaderpour
Iet Conference Proceedings, 2023 - An Efficient JAYA-Based Clustering Technique
Prabhu Prasad Dev, Priya Mishra, Anasua Banerjee
Lecture Notes in Networks and Systems, 2021 - An Enhanced Dynamic Image Watermarking Framework based on Phase Congruency and Saliency
Manas Ranian Nayak, Dinak Kumar Sahoo, Jyoti Prakash Sahoo, Lalit Mohan Satapathy, Prabhu Prasad Dev
2021 International Conference in Advances in Power Signal and Information Technology Apsit 2021, 2021
RECENT SCHOLAR PUBLICATIONS
- Testing Privacy-Preserving AI-Generated Text Detection Using Large Language Models
M Prajapati, SK Baliarsingh, JP Mohanty, PP Dev, J Hota, MR Biswal
2026 International Conference on Emerging Systems and Intelligent Computing … , 2026
2026 - Detecting AI-generated essays using fine-tuned XLNet-CNN hybrid techniques: a study of the academic integrity challenge
M Prajapati, SK Baliarsingh, PP Dev
International Journal of Machine Learning and Cybernetics 17 (2), 65 , 2026
2026 - Detecting AI-generated text in high-resource languages: developing a RoBERTa-CNN hybrid model for academic integrity challenge
M Prajapati, SK Baliarsingh, PP Dev
International Journal of Machine Learning and Cybernetics 17 (2), 40 , 2026
2026 - Cross-modal uncertainty modeling framework for unseen video anomaly detection
PP Dev, P Das, R Hazari
Neurocomputing, 132591 , 2026
2026
Citations: 1 - Real-Time Pose Estimation Using Lightweight High Resolution Network
S Kumar, PP Dev, JP Mohanty, SK Baliarsingh, J Hota
2025 OITS International Conference on Information Technology (OCIT), 402-407 , 2025
2025 - Multi-Attribute AI-based Storytelling Framework with IoT Deployment for Real-Time Narration: A Parameter-Efficient Approach
S Nayak, S Sharma, A Behura, PP Dev, JK Rout, M Priyadarsini
2025 13th International Conference on Intelligent Systems and Embedded … , 2025
2025 - A modified Gray Wolf Optimization algorithm for early detection of Parkinson’s Disease
K Santhosh, PP Dev, Z Lynton, P Das, E Ghaderpour
Biomedical Signal Processing and Control 109, 108061 , 2025
2025
Citations: 14 - CA-VAD: Caption Aware Video Anomaly Detection in surveillance videos
DP Senapati, SK Pani, SK Baliarsingh, PP Dev, HK Tripathy
Journal of Visual Communication and Image Representation 111, 104521 , 2025
2025
Citations: 3 - MSPL-VAD: Multi-Stage Pseudo-Labeling framework for Video Anomaly Detection
DP Senapati, SK Pani, SK Baliarsingh, MR Nayak, PP Dev
2025 International Conference on Innovations in Intelligent Systems … , 2025
2025
Citations: 1 - Dynamic Time Slice Prediction in Round Robin CPU Scheduling using Machine Learning
BK Dash, PP Dev, SK Pani
2025 International Conference on Emerging Systems and Intelligent Computing … , 2025
2025 - Detecting AI-Generated Text Using Fine-Tuned Transformers: A Study on Academic Integrity
M Prajapati, SK Baliarsingh, PP Dev, BM Saleh, J Hota, MR Biswal
International Conference on Advanced Network Technologies and Intelligent … , 2024
2024
Citations: 5 - CFViT: Coarse and fine-grained vision transformer for vehicle re-identification
SP Sinha, PP Dev, SK Baliarsingh, RA Behera, JP Mohanty
2024 OITS International Conference on Information Technology (OCIT), 234-239 , 2024
2024
Citations: 1 - Brain Tumour Classification: A Comparative Analysis of CNN Models and Generalisation Across Datasets
A Manna, A Saha, J Jain, A Kamal, SK Baliarsingh, PP Dev
2024 OITS International Conference on Information Technology (OCIT), 357-362 , 2024
2024 - STFANet: Learning Spatio-Temporal Feature Aggregation for Person Re-Identification
RA Behera, PP Dev, SK Baliarsingh, SP Sinha, MR Biswal
2024 OITS International Conference on Information Technology (OCIT), 228-233 , 2024
2024 - MCANet: Multimodal caption aware training-free video anomaly detection via large language model
PP Dev, R Hazari, P Das
International Conference on Pattern Recognition, 362-379 , 2024
2024
Citations: 12 - ReFLIP-VAD: Towards weakly supervised video anomaly detection via vision-language model
PP Dev, R Hazari, P Das
IEEE Transactions on Circuits and Systems for Video Technology , 2024
2024
Citations: 14 - Weakly Supervised Temporal Attention Framework for Video Anomaly Detection
MR Biswal, PP Dev, SK Baliarsingh
2024 15th International Conference on Computing Communication and Networking … , 2024
2024 - Temporal relation-embedded transformer for weakly-supervised video anomaly detection
T Chowdhury, PP Dev, SK Baliarsingh, JP Mohanty, MR Biswal
2024 11th International Conference on Signal Processing and Integrated … , 2024
2024
Citations: 2 - A smartphone-based deep learning framework for early detection of oral cancer signs
SK Baliarsingh, PP Dev, A Bandyopadhyay, AK Dash, R Pradhan
2024 International Conference on Emerging Systems and Intelligent Computing … , 2024
2024
Citations: 2 - CNNViT: A robust deep neural network for video anomaly detection
N Garuda, G Prasad, PP Dev, P Das, E Ghaderpour
IET Conference Proceedings CP870 2023 (39), 13-22 , 2023
2023
Citations: 8
MOST CITED SCHOLAR PUBLICATIONS
- A modified Gray Wolf Optimization algorithm for early detection of Parkinson’s Disease
K Santhosh, PP Dev, Z Lynton, P Das, E Ghaderpour
Biomedical Signal Processing and Control 109, 108061 , 2025
2025
Citations: 14 - ReFLIP-VAD: Towards weakly supervised video anomaly detection via vision-language model
PP Dev, R Hazari, P Das
IEEE Transactions on Circuits and Systems for Video Technology , 2024
2024
Citations: 14 - MCANet: Multimodal caption aware training-free video anomaly detection via large language model
PP Dev, R Hazari, P Das
International Conference on Pattern Recognition, 362-379 , 2024
2024
Citations: 12 - CNNViT: A robust deep neural network for video anomaly detection
N Garuda, G Prasad, PP Dev, P Das, E Ghaderpour
IET Conference Proceedings CP870 2023 (39), 13-22 , 2023
2023
Citations: 8 - Msdeepnet: A novel multi-stream deep neural network for real-world anomaly detection in surveillance videos
PP Dev, P Das, R Hazari
International Conference on Deep Learning Theory and Applications, 157-172 , 2023
2023
Citations: 6 - An Early diagnosis of diabetic retinopathy using ConvNeXt
Devanshi, SK Baliarsingh, PP Dev
2023 10th International Conference on Signal Processing and Integrated … , 2023
2023
Citations: 6 - Detecting AI-Generated Text Using Fine-Tuned Transformers: A Study on Academic Integrity
M Prajapati, SK Baliarsingh, PP Dev, BM Saleh, J Hota, MR Biswal
International Conference on Advanced Network Technologies and Intelligent … , 2024
2024
Citations: 5 - CA-VAD: Caption Aware Video Anomaly Detection in surveillance videos
DP Senapati, SK Pani, SK Baliarsingh, PP Dev, HK Tripathy
Journal of Visual Communication and Image Representation 111, 104521 , 2025
2025
Citations: 3 - Temporal relation-embedded transformer for weakly-supervised video anomaly detection
T Chowdhury, PP Dev, SK Baliarsingh, JP Mohanty, MR Biswal
2024 11th International Conference on Signal Processing and Integrated … , 2024
2024
Citations: 2 - A smartphone-based deep learning framework for early detection of oral cancer signs
SK Baliarsingh, PP Dev, A Bandyopadhyay, AK Dash, R Pradhan
2024 International Conference on Emerging Systems and Intelligent Computing … , 2024
2024
Citations: 2 - DG-GAN: A Deep Neural Network for Real-World Anomaly Detection in Surveillance Videos
DP Senapati, PP Dev, SK Baliarsingh, S Nayak, MR Biswal
International Conference on Advanced Network Technologies and Intelligent … , 2023
2023
Citations: 2 - Retinal and semantic segmentation of diabetic retinopathy images using MobileNetV3
M Prajapati, SK Baliarsingh, J Hota, PP Dev, S Das
2023 International Conference on Computer, Electrical & Communication … , 2023
2023
Citations: 2 - An Efficient JAYA-Based Clustering Technique
PP Dev, P Mishra, A Banerjee
Communication Software and Networks: Proceedings of INDIA 2019, 657-663 , 2020
2020
Citations: 2 - Cross-modal uncertainty modeling framework for unseen video anomaly detection
PP Dev, P Das, R Hazari
Neurocomputing, 132591 , 2026
2026
Citations: 1 - MSPL-VAD: Multi-Stage Pseudo-Labeling framework for Video Anomaly Detection
DP Senapati, SK Pani, SK Baliarsingh, MR Nayak, PP Dev
2025 International Conference on Innovations in Intelligent Systems … , 2025
2025
Citations: 1 - CFViT: Coarse and fine-grained vision transformer for vehicle re-identification
SP Sinha, PP Dev, SK Baliarsingh, RA Behera, JP Mohanty
2024 OITS International Conference on Information Technology (OCIT), 234-239 , 2024
2024
Citations: 1 - IoT-Based Smart Irrigation System for Optimal Water-Resource Utilization in Indian Agriculture
A Bhoi, SK Baliarsingh, PP Dev, U Ghugar, MR Biswal
2023 OITS International Conference on Information Technology (OCIT), 278-283 , 2023
2023
Citations: 1 - An Enhanced Dynamic Image Watermarking Framework based on Phase Congruency and Saliency
MR Nayak, DK Sahoo, JP Sahoo, LM Satapathy, PP Dev
2021 International Conference in Advances in Power, Signal, and Information … , 2021
2021
Citations: 1 - Testing Privacy-Preserving AI-Generated Text Detection Using Large Language Models
M Prajapati, SK Baliarsingh, JP Mohanty, PP Dev, J Hota, MR Biswal
2026 International Conference on Emerging Systems and Intelligent Computing … , 2026
2026 - Detecting AI-generated essays using fine-tuned XLNet-CNN hybrid techniques: a study of the academic integrity challenge
M Prajapati, SK Baliarsingh, PP Dev
International Journal of Machine Learning and Cybernetics 17 (2), 65 , 2026
2026
