Applying the transfer learning models on the dataset on the effect of diseases on Nagvel-betel (Piper betle) leaves Milind Gayakwad, Rahul Joshi, Tulshihar Patil, Pratvina Talele, Gurunath S. Waghale, Rajendra Pawar, Nidhi Poonia, Sachin Kadam, Priyanka Paygude Data in Brief, 2025 The dataset of Betel leaves includes 4156 leaves affected by various diseases. These diseases include Leaf Spot, Powdery Mildew, Anthracnose, Bacterial Blight, Cercospora Leaf Spot, Sooty Mold, Downy Mildew, Wilt Disease, Rust Disease, Mosaic Virus, Black Rot, Root Rot, Stem Canker, Leaf Curl Disease, and Fusarium Wilt. The camera is used to collect high-resolution images to ensure the exact detection of the images to detect diseases. The resolution of the photos was 3000 × 4000, consuming approximately 3 mb. The data set covers a wide range of diseases, and many samples were collected under each category. The dataset is saved using a hierarchical data structure, as the name of the folder indicates the label or category of the image. The reuse and recreation of this type of dataset are ensured by mapping the name of the disease with the apparent characters of the disease on the leaves. The experiment was performed using Vision Transformer Models to check the robustness of the dataset. The result of the classification report states that the range of accuracy varies from 0.7 to 0.9.
Sign language detection dataset: A resource for AI-based recognition systems Bindu Garg, Manisha Kasar, Priyanka Paygude, Amol Dhumane, Srinivas Ambala, Jitendra Rajpurohit, Abhay Sharma, Vidula Meshram, Amber Vats, Achyut Kashyap Data in Brief, 2025 Sign language is a very important mode of communication among deaf and hard-of-hearing populations. Automatic sign language detection based on deep learning model is the theme of this study. Hand gestures are classified by the Convolutional Neural Network (CNN) model to different signs. For training purposes, there are 26,000 images available with 3000 images for every alphabet letter such that there is complete representation of sign language gesture. Photos were taken in controlled lighting with a consistent black background to facilitate better feature extraction. The data contains varied participants of various age groups, skin types, and hand shapes to enhance generalization. Data collection was standardized through iPhone 15 Pro Max, black background cloth, tripod stand, and remote-controlled Drodcam app to maintain consistency in image quality and framing. For diversity and realism, three participants were involved in data collection, each providing 1000 images per sign, resulting in a rich and diverse dataset. Preprocessing of data methods were used for achieving the best quality of data, such as resizing, conversion to grayscale, normalization, and augmentation. Different techniques of data augmentation like rotation, flipping, scaling, brightness change, and addition of Gaussian noise were used to introduce variations in hand gestures and make the model robust against various environmental conditions. The dataset was then partitioned into 70 % training, 15 % validation, and 15 % test sets for maximizing model performance and ensuring good generalization. The dataset show high accuracy, reflecting the potential of the model for real-world usage, such as accessibility tools for the deaf community, educational tools, and real-time sign language recognition systems.
Machine-driven techniques for early-stage tumor identification and categorization in Digital Mammography: A comprehensive overview Ravindra Moje, Harshada Mhetre, Mangal Patil, Prashant Chougule, Pramod Jadhav, Priyanka Paygude, Shwetambari Chiwhane Journal of Integrated Science and Technology, 2025 Breast cancer remains a critical research focus in medical image analysis, being a leading cause of mortality among women. Digital mammography enhances early detection accuracy, crucial for improved prognosis. By 2020, breast cancer is projected to account for 25% of all cancer cases, characterized by uncontrolled cell proliferation in breast tissue. X-ray imaging can reveal tumor formation, with malignancy defined by metastatic potential. Traditional diagnostic approaches, often time-consuming and operator-dependent, necessitate more efficient detection methods. This study proposes an innovative deep learning-based classification system for automated breast cancer identification using biopsy images. The model's performance is evaluated using statistical metrics including precision, recall, and accuracy. By addressing key challenges in AI-assisted risk assessment, this research aims to accelerate the integration of advanced predictive tools, potentially optimizing and personalizing mammography screening programs in the future.
Exploring Language Preferences in Engineering Degrees 16th International Conference on Advances in Computing Control and Telecommunication Technologies Act 2025, 2025
Self-Driving Electrical Car Simulation using Mutation and DNN Priyanka Paygude, Sonali Idate, Milind Gayakwad, Namita Shinde, Chetan More, Amit Patil, Rahul Joshi, Kalyani Kadam, Anand Shinde Ssrg International Journal of Electronics and Communication Engineering, 2023
Real Time Traffic Control Using Big Data Analytics Rauhil Verma, Priyanka Paygude, Snehal Chaudhary, Sonali Idate 2018 International Conference on Advances in Communication and Computing Technology Icacct 2018, 2018
Prioritizing User Requirements for Agile Software Development Samridhi Sachdeva, Akshay Arya, Priyanka Paygude, Snehal Chaudhary, Sonali Idate 2018 International Conference on Advances in Communication and Computing Technology Icacct 2018, 2018
Use of data mining in crop yield prediction Shruti Mishra, Priyanka Paygude, Snehal Chaudhary, Sonali Idate Proceedings of the 2nd International Conference on Inventive Systems and Control Icisc 2018, 2018
Comparative evaluation of Pixel-Based and Object-Based classification approaches for Land Use/Land Cover mapping using deep learning on satellite data A Kumar, AK Ranjan, P Paygude, R Daimary Applied Geomatics 18 (1), 16 , 2026 2026 Citations: 5
CNN-Based Image Classification of Silkworm for Early Prediction of Diseases K Mungase, S Chiwhane, P Paygude Computer Sciences & Mathematics Forum 12 (1), 14 , 2025 2025 Citations: 1
Optimizing Dental Radiograph Quality with an Improved Wiener Filter: A PSNR and SSIM-Based Analysis P Shinde, P Paygude, S Dasman International Conference on Computational Intelligence and Soft Computing … , 2025 2025
Learning System for Early Detection of Mental Illness Using Social and Personal Parameters P Paygude, M Kasar, B Garg, H Mhetre, N Shinde, R Bhagwat, S Mali, ... University of Bahrain , 2025 2025
Health Plan Optimizer: A Regression-Based Approach with Grid Search Tuning V Bidve, K Kakade, P Paygude, R Bidwe, M Kasar University of Bahrain , 2025 2025
Plant Derived Nanoporous Carbon Materials: A Brief Review On Sustainable Alternative With Advance Applications. SD Mali, Y Chendake, M Bewoor, VR Patil, P Paygude Metallurgical & Materials Engineering 31 (5), 646 , 2025 2025
Applying the Transfer Learning Models on the Dataset on the effect of diseases on Nagvel-betel (Piper betle) leaves. M Gayakwad, R Joshi, T Patil, P Talele, GS Waghale, R Pawar, N Poonia, ... Data in Brief, 111987 , 2025 2025 Citations: 1
Sign language detection dataset: A resource for AI-based recognition systems B Garg, M Kasar, P Paygude, A Dhumane, S Ambala, J Rajpurohit, ... Data in Brief 61, 111703 , 2025 2025 Citations: 3
Real-Time Forest Fire Detection Using ESP32 Microcontroller with Cloud-Integrated Monitoring System A Kumar, L Upadhyay, P Pranjal, P Paygude 2025 IEEE North-East India International Energy Conversion Conference and … , 2025 2025 Citations: 1
Evolution of Automated Penetration Testing: Toolchains, Integration Strategies, and Operational Challenges. V Bidve, K Kakade, P Paygude, RV Bidwe, S Sangve, A Gangadhara International Journal of Safety & Security Engineering 15 (7) , 2025 2025
AI-Powered Breast Cancer Detection: A Comparative Study of Machine Learning and Deep Learning. R Kande, M Chhatre, R Bhagwat, K Dubey, G Joshi, P Paygude Mathematical Modelling of Engineering Problems 12 (6) , 2025 2025
Advanced comparative analysis of machine learning algorithms for early Parkinson's disease detection using vocal biomarkers A Kumar, JP Singh, P Paygude, R Daimary, S Prasad Digital Health 11, 20552076251342878 , 2025 2025 Citations: 8
Precision Agriculture in Sugarcane: Review of Disease Detection and Severity Classification Methods A Kanade, P Paygude 2025 12th International Conference on Computing for Sustainable Global … , 2025 2025
Survey and Comparative Study of Deep Learning Models for Indian Sign Language to Text Conversion N Janu, V Kumar, S Majumder, P Paygude, A Kumar International Symposium on Artificial Intelligence, 469-481 , 2025 2025
Machine-driven techniques for early-stage tumor identification and categorization in Digital Mammography: A comprehensive overview R Moje, H Mhetre, M Patil, P Chougule, P Jadhav, P Paygude, ... Journal of Integrated Science and Technology 13 (5), 1105-1105 , 2025 2025
Trust chain: A private blockchain for secure data exchange H Hemane, V Kaduskar, G Taxali, A Rajput, M Patil, P Paygude, H Mhetre, ... Journal of Integrated Science and Technology 13 (4), 1083-1083 , 2025 2025 Citations: 2
Species identification for Indian seafood markets: A machine learning approach with a fish dataset P Paygude, N Shinde, A Dhumane, GS Navale, P Chavan, A Kathole, ... Data in Brief 58, 111209 , 2025 2025 Citations: 5
Deep Learning Model to Evaluate Alzheimer's disease Through Multi-View Clustering S Nimbare, P Paygude, A Dhumane, S Rathi, V Bidve International Research Journal of Multidisciplinary Technovation 7 (1), 33-46 , 2025 2025 Citations: 4
Leveraging real-time data: A location-based ambulance booking and tracking system with geofencing P Chavan, P Paygude, S Rathi, M Patil, T Patil, S Jamdade, R Patil Journal of Integrated Science and Technology 13 (2), 1039-1039 , 2025 2025 Citations: 6
Learning style prediction of e-learner using hybrid optimizer-based neural network S Rathi, P Paygude, N Shaikh, S Sawant-Patil, T Patil, R Patil Journal of Integrated Science and Technology 13 (1), 1007-1007 , 2025 2025 Citations: 5
MOST CITED SCHOLAR PUBLICATIONS
Use of data mining in crop yield prediction S Mishra, P Paygude, S Chaudhary, S Idate 2018 2nd International Conference on Inventive Systems and Control (ICISC … , 2018 2018 Citations: 86
Techniques to secure data on cloud: Docker swarm or kubernetes? A Modak, SD Chaudhary, PS Paygude, SR Ldate 2018 Second international conference on inventive communication and … , 2018 2018 Citations: 59
Automated data validation testing tool for data migration quality assurance P Paygude, PR Devale Int J Mod Eng Res 3 (1), 599-603 , 2013 2013 Citations: 31
Prioritizing user requirements for agile software development S Sachdeva, A Arya, P Paygude, S Chaudhary, S Idate 2018 International Conference On Advances in Communication and Computing … , 2018 2018 Citations: 19
A dataset revolutionizing Indian bay leaf analysis P Paygude, S Thite, A Kumar, A Bhosle, R Pawar, R Mane, R Joshi, ... Data in Brief 57, 111024 , 2024 2024 Citations: 13
Dried fish dataset for Indian seafood: A machine learning application P Paygude, M Gayakwad, D Wategaonkar, R Pawar, R Pujeri, R Joshi Data in Brief 55, 110563 , 2024 2024 Citations: 10
Tourview: Sentiment based analysis on tourist domain D Sharma, A Kulshreshtha, P Paygude International Journal of Computer Science and Information Technologies 6 (3 … , 2015 2015 Citations: 10
A method to enhance privacy preservation in cloud storage through a three-layer scheme for computational intelligence in fog computing S Ojha, P Paygude, A Dhumane, S Rathi, V Bidve, A Kumar, P Devale MethodsX 13, 103053 , 2024 2024 Citations: 9
Use of evolutionary algorithm in regression test case prioritization: A review P Paygude, SD Joshi International conference on Computer Networks, Big data and IoT, 56-66 , 2020 2020 Citations: 9
Advanced comparative analysis of machine learning algorithms for early Parkinson's disease detection using vocal biomarkers A Kumar, JP Singh, P Paygude, R Daimary, S Prasad Digital Health 11, 20552076251342878 , 2025 2025 Citations: 8
Automation of data validation testing for QA in the project of DB migration P Paygude, PR Devale International Journal of Computer Science 3 (2), 15-22 , 2013 2013 Citations: 8
Leveraging real-time data: A location-based ambulance booking and tracking system with geofencing P Chavan, P Paygude, S Rathi, M Patil, T Patil, S Jamdade, R Patil Journal of Integrated Science and Technology 13 (2), 1039-1039 , 2025 2025 Citations: 6
Varying views of maxillary and mandibular aspects of teeth: A dataset S Chaudhary, P Shah, P Paygude, S Chiwhane, P Mahajan, P Chavan, ... Data in Brief 56, 110772 , 2024 2024 Citations: 6
Optimizing hyperparameters for enhanced LSTM-Based prediction system performance P Paygude, P Chavan, M Gayakwad, K Gupta, S Joshi, G Gopika, R Joshi, ... International Journal on Recent and Innovation Trends in Computing and … , 2023 2023 Citations: 6
Compassion driven conversational chatbot aimed for better mental health S Khadikar, P Sharma, P Paygude Zeich J 6 (9), 121-127 , 2020 2020 Citations: 6
Comparative evaluation of Pixel-Based and Object-Based classification approaches for Land Use/Land Cover mapping using deep learning on satellite data A Kumar, AK Ranjan, P Paygude, R Daimary Applied Geomatics 18 (1), 16 , 2026 2026 Citations: 5
Species identification for Indian seafood markets: A machine learning approach with a fish dataset P Paygude, N Shinde, A Dhumane, GS Navale, P Chavan, A Kathole, ... Data in Brief 58, 111209 , 2025 2025 Citations: 5
Learning style prediction of e-learner using hybrid optimizer-based neural network S Rathi, P Paygude, N Shaikh, S Sawant-Patil, T Patil, R Patil Journal of Integrated Science and Technology 13 (1), 1007-1007 , 2025 2025 Citations: 5
Comparative analysis of test case prioritization approaches in regression testing Paygude, P., Joshi, S., Bhattacharyya, D. International Journal of Advanced Trends in Computer Science and Engineering … , 2019 2019 Citations: 5
Real time traffic control using big data analytics R Verma, P Paygude, S Chaudhary, S Idate 2018 International Conference On Advances in Communication and Computing … , 2018 2018 Citations: 5