Dr. Prajna Parimita Dash

Scopus Publications

Development of a Neurofeedback System for Movement Imagery-Based BCI
Manoj Kumar Mukul, Ayush Chandra, Prajna Parimita Dash, Aminul Islam
Ssrg International Journal of Electronics and Communication Engineering, 2026
In recent decades, Brain Research–Computer Interfaces (BCIs) based on Electroencephalograms (EEGs) have become a crucial area of study, particularly for enabling real-time control of electric wheelchairs for individuals with disabilities. A most commonly used approach for this purpose is Movement Imagery (MI). Researchers have proposed various techniques to improve classification accuracy, focusing on effective preprocessing and feature extraction methods for real-time classification of movement imagery. This paper investigates the effectiveness of Empirical Mode Decomposition (EMD) as a preprocessing technique to decompose raw EEG signals into Intrinsic Mode Functions (IMFs) and evaluates suitable power spectrum estimation methods. Different rhythmic bands of the raw EEG signals are selected for EMD decomposition. The resulting IMFs are then used to estimate power spectral density using parametric (Burg method) and non-parametric (Welch method) approaches. The analyzed feature is the average power within the rhythmic bands of the selected IMFs. The outcomes of this study have multiple observations. The reported results indicate that the Welch method outperforms the Burg method, achieving overall classification accuracy that is more than 1% higher. Additionally, the proposed methods achieve good classification accuracy on standard movement imagery datasets but fail to match the performance of BCI-illiterate subjects. Based on this analysis, the authors conclude that signal processing and feature extraction methods alone are insufficient to achieve high classification accuracy, emphasizing that users of BCI technology require proper training.
Deep learning approaches for detecting malignant melanoma in dermoscopic imagery
Abhishek Thakur, Sudhansu Kumar Mishra, Monica Bhutani, Prajna Parimita Dash, Prabhat Kumar Upadhyay, et al.
International Journal of Information Technology Singapore, 2026
Enhancing non-orthogonal multiple access systems: A reconfigurable Machine Learning classification approach
Saurabh Srivastava, Rampravesh Kumar, Prajna Parimita Dash
Engineering Applications of Artificial Intelligence, 2025
Secure Image Encryption with Optimized Chaotic Sequences and Multi-layer Cryptographic Operations
Jagannath Sethi, Sudhansu Kumar Mishra, Prajna Parimita Dash, Monica Bhutani
SN Computer Science, 2025
GAN-CNN based Structure-Preserving Mixed Noise Removal Model for Enhancing Medical Image
Journal of Scientific and Industrial Research, 2025
Global perspectives on digital twin adoption in healthcare
Saurabh Srivastava, Prajna Parimita Dash
Digital Twin Technology for Better Health A Healthcare Odyssey, 2025
Entropy Enhanced Bilateral Filter for Denoising Medical Images with Variable Region of Interest
Dikshant Vats, Sunny Kumar, Tanmay Arora, Vishal H. Shah, Prajna Parimita Dash
Lecture Notes in Networks and Systems, 2025
Low Resolution Medical Image Enhancement using Generative Artificial Intelligence
Vishal H Shah, Abhishek Kumar Mishra, Nilanshu Chandra, Shivam Kumar, Prajna Parimita Dash
3rd International Conference on Intelligent Data Communication Technologies and Internet of Things Idciot 2025, 2025
Accurate diagnosis through medical image data is the base of proper prognosis in healthcare, which requires high-quality medical image. Enhancement of various low-resolution medical images in healthcare needs attention. The research addresses the challenge of generating high-resolution images from low-resolution inputs, a critical difficulty in picture super-resolution. Super-Resolution GAN (SRGAN), which enhances image quality through perceptual loss to produce visually realistic and high-resolution outputs, has been employed. Through experiments and evaluation, we demonstrated the effectiveness of SRGAN compared to other variants of GAN in producing realistic, high-resolution images, showcasing the advancements made in image generation tasks using GANs.
Constellation design for PD-NOMA-based mmWave inter-satellite communication
Saurabh Srivastava, Prajna Parimita Dash, Deepak Kumar Rout, Dinesh Madhukar Chandwadkar, Sunita Pandit Ugale
Computers and Electrical Engineering, 2024
Two stage self-adaptive cognitive neural network for mixed noise removal from medical images
Vishal H Shah, Prajna Parimita Dash
Multimedia Tools and Applications, 2024
GP-based fair power allocation for 6G multi-user power domain NOMA network
Saurabh Srivastava, Prajna Parimita Dash
Journal of Ambient Intelligence and Humanized Computing, 2024
ML-based reconfigurable symbol decoder: An alternative for next-generation communication systems
Saurabh Srivastava, Prajna Parimita Dash
Engineering Applications of Artificial Intelligence, 2022
Decisive Analysis of Fixed Power Allocation Coefficients in a PD-NOMA Network
Saurabh Srivastava, Prajna Parimita Dash, Sanjay Kumar
Proceedings of 4th International Conference on Cybernetics Cognition and Machine Learning Applications Icccmla 2022, 2022
Coefficient-Scaling-Based Fair Power Allocation for Multi-User Power-Domain Nonorthogonal Multiple Access Network
Saurabh Srivastava, Prajna Parimita Dash
Journal of Circuits Systems and Computers, 2021
Interactive teaching learning based optimization technique for multiple object tracking
Prajna Parimita Dash, Sudhansu Kumar Mishra, Kishore Kumar Senapati, Ganapati Panda
Multimedia Tools and Applications, 2021
Capacity analysis of non-orthogonal multiple access for uplink and downlink
Saurabh Srivastava, Prajna Parimita Dash, Sanjay Kumar
Journal of Mobile Multimedia, 2021
Non-Orthogonal Multiple Access: Procession towards B5G and 6G
Saurabh Srivastava, Prajna Parimita Dash
IEEE 2nd International Conference on Applied Electromagnetics Signal Processing and Communication Aespc 2021 Proceedings, 2021
Identification of real-time maglev plant using long-short term memory network based deep learning technique
Journal of Scientific and Industrial Research, 2020
An efficient hybrid framework for visual tracking using Exponential Quantum Particle Filter and Mean Shift optimization
Prajna Parimita Dash, Dipti Patra
Multimedia Tools and Applications, 2020
Analysis of NOMA: In capacity domain
International Symposium on 5g Beyond for Rural Upliftment 2020 in Twinning Activity Between BIT Sindri Iit Ism Dhanbad Jointly with the IEEE 5g Summit and 35th Gisfi Standardization Series Meeting Gssm, 2020
Animal tracking in wildlife footage with quantum particle filter (QPF)
Prajna Parimita Dash, Sudhansu Kumar Mishra, Dipti Patra
Proceedings 2019 International Conference on Information Technology Icit 2019, 2019
Mutation based self regulating and self perception particle swarm optimization for efficient object tracking in a video
Prajna Parimita Dash, Dipti Patra
Measurement Journal of the International Measurement Confederation, 2019
Efficient visual tracking using multi-feature regularized robust sparse coding and quantum particle filter based localization
Prajna Parimita Dash, Dipti Patra
Journal of Ambient Intelligence and Humanized Computing, 2019
Moment Invariant Based Weed/Crop Discrimination for Smart Farming
Sabiha Fatma, Prajna Parimita Dash
2019 International Conference on Computer Electrical and Communication Engineering Iccece 2019, 2019
GCD Based Blind Super-Resolution for Remote Sensing Applications
Neerav Sharma, Praina Parimita Dash, Priyank Saxena
2nd International Conference on Energy Power and Environment Towards Smart Technology Icepe 2018, 2018
Efficient object tracking using local tetra pattern based texture feature
Prajna Parimita Dash, Dipti Patra
2015 IEEE International Conference on Computer Graphics Vision and Information Security Cgvis 2015, 2016
Local binary pattern as a texture feature descriptor in object tracking Algorithm
Prajna Parimita Dash, Dipti Patra, Sudhansu Kumar Mishra
Advances in Intelligent Systems and Computing, 2014
Robust detection & tracking of object by particle filter using color information
Ashwani Kumar, Sudhanshu Kumar Mishra, Pranjna Parimita Dash
2013 4th International Conference on Computing Communications and Networking Technologies Icccnt 2013, 2013
Ohta based covariance technique for tracking object in video scene
Prajna Parimita Dash, Santhosh Aitha, Dipti Patra
2012 IEEE Students Conference on Electrical Electronics and Computer Science Innovation for Humanity Sceecs 2012, 2012
Evolutionary neural network for noise cancellation in image data
Prajna Parimita Dash, Dipti Patra
International Journal of Computational Vision and Robotics, 2011

Dr. Prajna Parimita Dash

EDUCATION

RESEARCH, TEACHING, or OTHER INTERESTS

Scopus Publications