Rashi Agarwal

Scopus Publications

HyCoSwin-PD: An explainable hybrid ConvNeXtV2-Swin transformer framework for Parkinson’s disease detection from neuroimaging
Vishal Awasthi, Hemant Kumar, Mamta Tiwari, Bhupender Singh Rawat, Brajesh Kumar Sharma, Shubhendra Singh, Rashi Agarwal
Methodsx, 2026
Accurate detection of Parkinson's disease (PD) from structural MRI remains a significant challenge due to the diffuse and heterogeneous nature of PD-related neuroanatomical alterations. This study introduces HyCoSwin-PD, an advanced hybrid deep learning framework that integrates ConvNeXt-V2 and Swin Transformer to jointly model fine-grained local morphology and hierarchical global context. ConvNeXt-V2 provides strong convolutional inductive biases for capturing subtle structural variations, whereas Swin Transformer contributes multi-scale contextual reasoning through window-based self-attention. A dedicated fusion mechanism unifies these complementary representations into a coherent latent space optimized for PD classification. Evaluated on the PPMI dataset, HyCoSwin-PD achieves 95.8% accuracy, 95.1% sensitivity, and 96.4% specificity, demonstrating superior diagnostic reliability. Ablation analyses further confirm the synergistic value of hybridizing convolutional and transformer-based encoders. Despite these promising outcomes, the reliance on a unimodal MRI dataset and a limited cohort underscores the need for multi-modal and multi-center validation. Overall, HyCoSwin-PD provides a robust, methodologically novel, and clinically relevant framework for MRI-based PD detection.•HyCoSwin-PD introduces a hybrid architecture that integrates ConvNeXt-V2 for local morphological encoding with Swin Transformer for hierarchical global context modeling.•The framework incorporates a feature fusion module that unifies heterogeneous representations to enhance discriminative capacity in MRI-based PD detection.
Analyzing the Proficiency of Deep Learning Techniques for Music Genre Classification
Agrima Malviya, Rashi Agarwal
Lecture Notes in Networks and Systems, 2026
Deep Learning for Deepfake Detection: A Multimodal Approach for Image and Video Forgery Identification
Rupali Singh, Rashi Agarwal
Lecture Notes in Networks and Systems, 2026
Enhanced Classification of Alzheimer’s Disease Using Advanced Machine Learning Models on Radiomics Features from 3D MRI
Hemant Kumar, Rashi Agarwal
Lecture Notes in Networks and Systems, 2026
Bio-inspired gloden jackal optimization of XGBoost model enhances 30-day sepsis mortality predictions
Hemant Kumar, Rashi Agarwal, Amit Yadav
Journal of Critical Care, 2025
NEMAEP: A NOVEL ENSEMBLE MACHINE LEARNING FRAMEWORK FOR ACCURATE EFFORT ESTIMATION IN SOFTWARE PROJECTS
Journal of Theoretical and Applied Information Technology, 2024
A hybrid efficientNetB0-XGBoost framework for efficient brain tumor classification using MRI images
Hemant Kumar, Digvijay Pandey, Amit Yadav, Rashi Agarwal, Shivneet Tripathi, Somesh Kumar Malhotra
Interdisciplinary Approaches to AI Internet of Everything and Machine Learning, 2024
Brain tumors pose significant challenges in medical diagnosis due to their diverse characteristics and critical impact on human health. This study proposes an advanced framework for brain tumor classification, integrating EfficientNet-B0 for feature extraction and XGBoost for classification. The preprocessing stage involves resizing, normalization, and data augmentation of brain MRI images to ensure high-quality input for the model. EfficientNet-B0's parameter efficiency and computational speed are leveraged to extract discriminative features, which are then classified using the XGBoost algorithm. Techniques such as Global Average Pooling and a dropout ratio of 0.3 are employed to enhance the model's robustness and mitigate overfitting. Experimental results on the Kaggle brain tumor dataset demonstrate the superiority of our approach, achieving an overall accuracy of 99.21%, precision of 99.18%, recall of 98.96%, and F1-score of 98.92%. This research shows that deep learning and machine learning can accurately and efficiently classify brain tumours, improving clinical diagnostic.
Transformer-based decoder of melanoma classification using hand-crafted texture feature fusion and Gray Wolf Optimization algorithm
Hemant Kumar, Abhishek Dwivedi, Abhishek Kumar Mishra, Arvind Kumar Shukla, Brajesh Kumar Sharma, Rashi Agarwal, Sunil Kumar
Methodsx, 2024
Melanoma is a type of skin cancer that poses significant health risks and requires early detection for effective treatment. This study proposing a novel approach that integrates a transformer-based model with hand-crafted texture features and Gray Wolf Optimization, aiming to enhance efficiency of melanoma classification. Preprocessing involves standardizing image dimensions and enhancing image quality through median filtering techniques. Texture features, including GLCM and LBP, are extracted to capture spatial patterns indicative of melanoma. The GWO algorithm is applied to select the most discriminative features. A transformer-based decoder is then employed for classification, leveraging attention mechanisms to capture contextual dependencies. The experimental validation on the HAM10000 dataset and ISIC2019 dataset showcases the effectiveness of the proposed methodology. The transformer-based model, integrated with hand-crafted texture features and guided by Gray Wolf Optimization, achieves outstanding results. The results showed that the proposed method performed well in melanoma detection tasks, achieving an accuracy and F1-score of 99.54% and 99.11% on the HAM10000 dataset, and an accuracy of 99.47%, and F1-score of 99.25% on the ISIC2019 dataset. • We use the concepts of LBP and GLCM to extract features from the skin lesion images. • The Gray Wolf Optimization (GWO) algorithm is employed for feature selection. • A decoder based on Transformers is utilized for melanoma classification.
ViT-HHO: Optimized vision transformer for diabetic retinopathy detection using Harris Hawk optimization
Vishal Awasthi, Namita Awasthi, Hemant Kumar, Shubhendra Singh, Prabal Pratap Singh, Poonam Dixit, Rashi Agarwal
Methodsx, 2024
Diabetic retinopathy (DR) is a significant cause of vision impairment globally, emphasizing the importance of timely and precise detection to prevent severe consequences. This study presents an optimized Vision Transformer (ViT) model that incorporates Harris Hawk Optimization (HHO) to improve the automated detection of diabetic retinopathy (DR). The ViT architecture utilizes self-attention mechanisms to capture local and global features in retinal images. Additionally, HHO optimizes key hyperparameters to maximize the performance of the model. The proposed ViT-HHO model achieved exceptional performance on the APTOS-2019 and IDRiD datasets. Specifically, it achieved 99.83 % accuracy, 99.78 % sensitivity, 99.85 % specificity, and 99.80 % AUC-ROC on the APTOS-2019 dataset, surpassing traditional CNNs and alternative optimization techniques. The model exhibited strong generalization on the IDRiID dataset, achieving an accuracy of 99.11 % and an AUC-ROC of 99.12 %. The ViT-HHO model demonstrates the potential for enhancing the clinical detection of diabetic retinopathy (DR), providing high precision and reliability.•An optimized Vision Transformer (ViT) model was developed using HHO for improved detection of Diabetic Retinopathy (DR).•The model was validated on the APTOS-2019 and IDRiID datasets, demonstrating superior accuracy and AUC-ROC metrics.•The model's generalization and robustness were demonstrated through comprehensive performance evaluations.
Unmasking VGG16: LIME Visualizations for Brain Tumor Diagnosis
Richa Tiwari, Rashi Agrawal
2024 IEEE International Conference on Computer Vision and Machine Intelligence Cvmi 2024, 2024
Brain tumors are complex and potentially life-threatening conditions requiring accurate diagnosis. This study explores using VGG16 CNN architecture to classify brain tumors in MRI scans. CNNs excel in image classification but lack transparency, raising concerns in critical applications like medical diagnosis. To address this, we use Explainable AI (XAI) techniques. We enhance interpretability using Superpixel images, Heatmaps, and Image Masks to visualize important features for predictions. Our approach achieves 98.8% accuracy, with visualizations aiding in understanding the model’s decisions and providing insights for medical professionals. This research contributes to XAI in medical imaging, showing the potential of combining deep learning with interpretable methods for healthcare decision-making.
Advances in Deep Learning for the Detection of Alzheimer’s Disease Using MRI—A Review
S. Hariharan, Rashi Agarwal
Studies in Computational Intelligence, 2024
ViT-ALZ: Vision Transformer with Deep Neural Network for Alzheimer’s Disease Detection
Hemant Kumar, Rashi Agarwal
Lecture Notes in Networks and Systems, 2024
Can ChatGPT Help in the Awareness of Diabetes?
Imran Khan, Rashi Agarwal
Annals of Biomedical Engineering, 2023
An Intelligent Framework for Estimating Software Development Projects using Machine Learning
Prateek Srivastava, Nidhi Srivastava, Rashi Agarwal, Pawan Singh
International Journal on Recent and Innovation Trends in Computing and Communication, 2023
Diabetic Retinopathy Segmentation in IDRiD using Enhanced U-Net
Rashi Agarwal
IEEE 1st International Conference on Ambient Intelligence Knowledge Informatics and Industrial Electronics Aikiie 2023, 2023
Diagnosis of COVID-19 Using Deep Learning Augmented with Contour Detection on X-rays
Rashi Agarwal, S. Hariharan
Lecture Notes in Networks and Systems, 2023
Incorporating Requirement Engineering into Agile Methodologies: Challenges and Proposed Solutions
Prateek Srivastava, Nidhi Srivastava, Rashi Agarwal, Pawan Singh
2023 9th International Conference on Signal Processing and Communication ICSC 2023, 2023
Integrated learning algorithms-based epileptologist assistive tool for seizure detection and prediction
Sripada Rama Sree, Rashi Agarwal, S. Markkandan, Suraya Mubeen, Manoj Ashok Wakchaure, Bal Krishna Saraswat
Soft Computing, 2023
Using Deep Learning Approach for Land-Use and Land-Cover Classification based on Satellite images
Rashi Agarwal, Silky Goel, Rahul Nijhawan
2022 2nd Asian Conference on Innovation in Technology Asiancon 2022, 2022
Human Disease Prognosis and Diagnosis Using Machine Learning
Sunil Kumar, Harish Kumar, Rashi Agarwal, V. K. Pathak
Lecture Notes in Electrical Engineering, 2022
Estimation in Agile Software Development Using Artificial Intelligence
Prateek Srivastava, Nidhi Srivastava, Rashi Agarwal, Pawan Singh
Lecture Notes in Networks and Systems, 2022
Audio-Visual Emotion Recognition System Using Multi-Modal Features
Anand Handa, Rashi Agarwal, Narendra Kohli
International Journal of Cognitive Informatics and Natural Intelligence, 2021
Facial expression recognition using local multidirectional score pattern descriptor and modified hidden Markov model
Mayur Rahul, Narendra Kohli, Rashi Agarwal
International Journal of Advanced Intelligence Paradigms, 2021
Incremental approach for multi-modal face expression recognition system using deep neural networks
Anand Handa, Rashi Agarwal, Narendra Kohli
International Journal of Computational Vision and Robotics, 2021
WEED IDENTIFICATION USING K-MEANS CLUSTERING WITH COLOR SPACES FEATURES IN MULTI-SPECTRAL IMAGES TAKEN BY UAV
Rashi Agarwal, S Hariharan, M. Nagabhushana Rao, Abhishek Agarwal
International Geoscience and Remote Sensing Symposium IGARSS, 2021
Covid-19 Analysis using Deep Learning Methods and Computed Tomography Scans
Rashi Agarwal, Rahul Nijhawan, Siddharth Gupta, Silky Goel
2021 IEEE Bombay Section Signature Conference Ibssc 2021, 2021
A multimodel keyword spotting system based on lip movement and speech features
Anand Handa, Rashi Agarwal, Narendra Kohli
Multimedia Tools and Applications, 2020
Facial expression recognition using local binary pattern and modified hidden Markov model
Mayur Rahul, Narendra Kohli, Rashi Agarwal
International Journal of Advanced Intelligence Paradigms, 2020
A comprehensive video dataset for multi-modal recognition systems
Anand Handa, Rashi Agarwal, Narendra Kohli
Data Science Journal, 2019
An efficient technique for facial expression recognition using multistage hidden markov model
Mayur Rahul, Pushpa Mamoria, Narendra Kohli, Rashi Agrawal
Advances in Intelligent Systems and Computing, 2019
Facial expression recognition using geometric features and modified hidden Markov model
Mayur Rahul, Narendra Kohli, Rashi Agarwal, Sanju Mishra
International Journal of Grid and Utility Computing, 2019
Partition based feature extraction technique for facial expression recognition using multi-stage hidden Markov model
Journal of Engineering and Applied Sciences, 2018
Facial expression recognition using multistage hidden markov model
Journal of Theoretical and Applied Information Technology, 2017
An easy method for leaf area estimation based on digital images
Madhu Jadon, Rashi Agarwal, Raghuraj Singh
2016 International Conference on Computational Techniques in Information and Communication Technologies Icctict 2016 Proceedings, 2016
Review of features and machine learning techniques for web searching
Neha Sharma, Rashi Agarwal, Narendra Kohli
11th International Conference on Industrial and Information Systems Iciis 2016 Conference Proceedings, 2016
A survey of face recognition techniques and comparative study of various bi-modal and multi-modal techniques
Anand Handa, Rashi Agarwal, Narendra Kohli
11th International Conference on Industrial and Information Systems Iciis 2016 Conference Proceedings, 2016
Automatic Building Detection From High-Resolution Satellite Images Based on Morphology and Internal Gray Variance
D. Chaudhuri, N. K. Kushwaha, A. Samal, R. C. Agarwal
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2016
Remote sensing methods for land cover assessment: Case study of jharia coal field
International Journal of Applied Engineering Research, 2015
Edge detection in images using modified bit-planes sobel operator
Rashi Agarwal
Advances in Intelligent Systems and Computing, 2014
A statistical approach for automatic detection of ocean disturbance features from SAR images
D. Chaudhuri, A. Samal, A. Agrawal, Sanjay, A. Mishra, V. Gohri, R. C. Agarwal
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2012
Bit plane average filtering to remove Gaussian noise from high contrast images
Rashi Agarwal
2012 International Conference on Computer Communication and Informatics Iccci 2012, 2012
Bit planes histogram equalization for tone mapping of high contrast images
Rashi Agarwal
Proceedings 2011 8th International Conference on Computer Graphics Imaging and Visualization CGIV 2011, 2011
Detection of coal mine fires in the Jharia coal field using NOAA/AVHRR data
Rashi Agarwal, D Singh, D S Chauhan, K P Singh
Journal of Geophysics and Engineering, 2006

RECENT SCHOLAR PUBLICATIONS

Progressive Evolution of Multimodal Architectures for Fake News Detection: From Independent Feature Fusion to Contrastive Cross-Modal Alignment
P Brijwal, M Yadav, A Singh, SP Singh, R Agarwal
Cureus Journals 3 (1) , 2026
2026
HyCoSwin-PD: An explainable hybrid ConvNeXtV2-Swin transformer framework for Parkinson’s disease detection from neuroimaging
V Awasthi, H Kumar, M Tiwari, BS Rawat, BK Sharma, S Singh, R Agarwal
MethodsX, 103868 , 2026
2026
Enhanced Classification of Alzheimer’s Disease Using Advanced Machine Learning Models on Radiomics Features from 3D MRI
H Kumar, R Agarwal
International Conference on Hybrid Intelligence: Theories and Applications … , 2026
2026
Comparative Analysis of Unmanned Aerial Vehicle and Ground-Level Data Using Computer Vision in Agriculture
SK Gupta, R Agarwal
Cureus Journals 2 (1) , 2025
2025
Deep Learning-Based Nutritional Analysis of Food Images Using EfficientNetB4 and Multilayer Perceptron
A Diwakar, R Agarwal
Cureus Journals 2 (1) , 2025
2025
for Interpretable Brain Tumor
R Tiwari, R Agarwal
Mathematics and Logics in Computer Science: Proceedings of ICMLCS 2024, 143 , 2025
2025
Deep Learning for Deepfake Detection: A Multimodal Approach for Image and Video Forgery Identification
R Singh, R Agarwal
International Conference on Data Analytics & Management, 412-421 , 2025
2025
Bio-inspired gloden jackal optimization of XGBoost model enhances 30-day sepsis mortality predictions
H Kumar, R Agarwal, A Yadav
Journal of Critical Care 87, 155013 , 2025
2025
Citations: 1
A hybrid EfficientNetB0-XGBoost framework for efficient brain tumor classification using MRI images
H Kumar, D Pandey, A Yadav, R Agarwal, S Tripathi, SK Malhotra
Interdisciplinary Approaches to AI, Internet of Everything, and Machine … , 2025
2025
Citations: 4
NEMAEP: A NOVEL ENSEMBLE MACHINE LEARNING FRAMEWORK FOR ACCURATE EFFORT ESTIMATION IN SOFTWARE PROJECTS
P SRIVASTAVA, N SRIVASTAVA, R AGARWAL, P SINGH
Journal of Theoretical and Applied Information Technology 102 (24) , 2024
2024
Citations: 1
ViT-HHO: Optimized vision transformer for diabetic retinopathy detection using Harris Hawk optimization
V Awasthi, N Awasthi, H Kumar, S Singh, PP Singh, P Dixit, R Agarwal
MethodsX 13, 103018 , 2024
2024
Citations: 18
Transformer-based decoder of melanoma classification using hand-crafted texture feature fusion and Gray Wolf Optimization algorithm
H Kumar, A Dwivedi, AK Mishra, AK Shukla, BK Sharma, R Agarwal, ...
MethodsX 13, 102839 , 2024
2024
Citations: 8
Analyzing the Proficiency of Deep Learning Techniques for Music Genre Classification
A Malviya, R Agarwal
International Conference on Communication and Intelligent Systems, 53-71 , 2024
2024
Unmasking VGG16: LIME visualizations for brain tumor diagnosis
R Tiwari, R Agrawal
2024 IEEE International Conference on Computer Vision and Machine … , 2024
2024
Citations: 7
Lrp-enhanced vgg16 model for interpretable brain tumor classification
R Tiwari, R Agarwal
International Conference on Mathematics and Logics in Computer Science, 143-160 , 2024
2024
Citations: 1
Epicardial Macro-Rentrant Tachycardia Involving the Septo-Pulmonary Bundle
R Agarwal, A Nguyen, R Kutieleh, R Mahajan
Heart, Lung and Circulation 33, S427-S428 , 2024
2024
An insight on artificial intelligence (AI) and Internet of Things (IoT) driven hydroponics farming
NS Bhandari, N Bhandari, R Agarwal, PK Sharma
2024 5th International Conference on Image Processing and Capsule Networks … , 2024
2024
Citations: 11
Advances in Deep Learning for the Detection of Alzheimer’s Disease Using MRI—A Review
S Hariharan, R Agarwal
Computational Intelligence in Healthcare Informatics, 363-388 , 2024
2024
Citations: 1
Advances in Deep Learning
S Hariharan, R Agarwal
Computational Intelligence in Healthcare Informatics, 363 , 2024
2024
Evaluation Of A Best Digital Supplier By Fuzzy SWARA-WASPAS Strategies
R Agarwal, A Agrawal, A Sharma, B Agrawal
Internatonal Journal of expermental research and revew 45, 203-211 , 2024
2024
Citations: 1

MOST CITED SCHOLAR PUBLICATIONS

Starting out with Python
T Gaddis, R Agarwal
Pearson Addison Wesley , 2009
2009
Citations: 93
Effect of stochastic noise on superior Julia sets
M Rani, R Agarwal
Journal of Mathematical Imaging and Vision 36 (1), 63-68 , 2010
2010
Citations: 64
Detection of coal mine fires in the Jharia coal field using NOAA/AVHRR data
R Agarwal, D Singh, DS Chauhan, KP Singh
Journal of Geophysics and engineering 3 (3), 212-218 , 2006
2006
Citations: 53
Facial expression recognition using geometric features and modified hidden Markov model
M Rahul, N Kohli, R Agarwal, S Mishra
International Journal of Grid and Utility Computing 10 (5), 488-496 , 2019
2019
Citations: 46
Weed identification using K-means clustering with color spaces features in multi-spectral images taken by UAV
R Agarwal, S Hariharan, MN Rao, A Agarwal
2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 7047 … , 2021
2021
Citations: 42
Minimum relevant features to obtain ai explainable system for predicting breast cancer in WDBC
R Agarwal, M Revanth
International Journal of Health Sciences 6 (!X) , 2022
2022
Citations: 33
Analysing mobile random early detection for congestion control in mobile ad-hoc network
S Sharma, D Jindal, R Agarwal
International Journal of Electrical and Computer Engineering 8 (3), 1305 , 2018
2018
Citations: 26
Antibacterial finish of textile using papaya peels derived silver nanoparticles
R Agarwal
2015
Citations: 25
Nano surface modification of poly (ethylene terephthalate) fabrics for enhanced comfort properties for activewear
R Agarwal, M Jassal, AK Agrawal
Journal of Industrial and Engineering Chemistry 98, 217-230 , 2021
2021
Citations: 24
Edge detection in images using modified bit-planes Sobel operator
R Agarwal
Proceedings of the Third International Conference on Soft Computing for … , 2014
2014
Citations: 22
Tomato disease detection using vision transformer with residual L1-norm attention and deep neural networks
M Tiwari, H Kumar, N Prakash, S Kumar, R Neware, S Tripathi, R Agarwal
International Journal of Intelligent Engineering & Systems 17 (1) , 2024
2024
Citations: 21
ML-based classifier for Sloan Digital Sky spectral objects
R Agarwal, N Rao
Neuroquantology 20 (6), 8329-8358 , 2022
2022
Citations: 21
Decision Support System designed to detect yellow mosaic in Pigeon pea using Computer Vision
R Agarwal, A Agarwal
Design Engineering, 832-844 , 2021
2021
Citations: 21
ViT-HHO: Optimized vision transformer for diabetic retinopathy detection using Harris Hawk optimization
V Awasthi, N Awasthi, H Kumar, S Singh, PP Singh, P Dixit, R Agarwal
MethodsX 13, 103018 , 2024
2024
Citations: 18
Durable functionalization of polyethylene terephthalate fabrics using metal oxides nanoparticles
R Agarwal, M Jassal, AK Agrawal
Colloids and Surfaces A: Physicochemical and Engineering Aspects 615, 126223 , 2021
2021
Citations: 18
Human disease prognosis and diagnosis using machine learning
S Kumar, H Kumar, R Agarwal, VK Pathak
Emerging Technologies for Computing, Communication and Smart Cities … , 2022
2022
Citations: 17
Facial expression recognition using local binary pattern and modified hidden Markov model
M Rahul, N Kohli, R Agarwal
International Journal of Advanced Intelligence Paradigms 17 (3-4), 367-378 , 2020
2020
Citations: 17
Can ChatGPT help in the awareness of diabetes?
I Khan, R Agarwal
Annals of biomedical engineering 51 (10), 2125-2129 , 2023
2023
Citations: 14
An approach for congestion control in mobile ad hoc networks
S Sharma, D Jindal, R Agarwal
International Journal of Emerging Trends in Engineering and Development 3 (7 … , 2017
2017
Citations: 14
Transfer Learning and Supervised Machine Learning Approach for Detection of Skin Cancer: Performance Analysis and Comparison
SK Hemant Kumar, Amit Virmani, Shivneet Tripathi, Rashi Agrawal
Drugs and Cell Therapies in Hematology 10 (No. 1 (2021)) , 2021
2021
Citations: 13

Rashi Agarwal

RESEARCH INTERESTS

Scopus Publications

RECENT SCHOLAR PUBLICATIONS

MOST CITED SCHOLAR PUBLICATIONS