Dr. G.S.Mate

@jspmrscoe.edu.in

Associate Professor

Dr. G.S.Mate


                        Download Compact PDF  
https://researchid.co/gsmate_it
Dr. G.S. Mate is an Associate Professor, at the Department of Information Technology, JSPM’s Rajarshi Shahu College of Engineering, Savitribai Phule Pune University, Maharashtra, India. She is having teaching experience of more than 23 years at Engineering College Her research interests include Image Processing, Neural Netwroks Machine Learning, Deep Learning. She has published more than 10 papers indexed in SCOPUS/Web of Science/UGC approved Journals/Conferences, etc. She is also a reviewer of International Journals/Conferences.

EDUCATION

PHD Elecronics ME Computer BEComputer

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Vision and Pattern Recognition, Human-Computer Interaction, Artificial Intelligence, Information Systems
33

Scopus Publications

152

Scholar Citations

6

Scholar h-index

4

Scholar i10-index

Scopus Publications

  • Enhanced speech emotion detection via Signed Cumulative Distribution Transform and Progressive Graph Convolutional Networks
    Seema Kedar, Pradnya Thakre, Archana Jadhav, Geetanjali S. Mate, Dipali Himmatrao Patil
    International Journal of Speech Technology, 2026
  • Utilizing game theory to develop innovative applications for enhancing communication system
    Vaishali Latke, Archana R. Panhalkar, G. S. Mate, Dipali Himmatrao Patil, Sardor Sabirov, Alaknanda S. Patil
    Journal of Discrete Mathematical Sciences and Cryptography, 2026
    The purpose of this paper’s study is to discover how game theory might be applied to develop innovative approaches for enhancing communication strategies. The research offers a strategic framework that conceptualises various communication entities as rational agents optimising resource utilisation and decision-making. Reward optimisation, cooperative and non-cooperative game models, and Nash equilibrium analysis can reduce interference and improve spectrum sharing. Simulated analysis improves throughput, fairness, and security more than traditional methods. The results show that game-theoretic solutions are robust, scalable, and flexible.
  • Lightweight AI-supported ECC algorithms for security in IoT and edge devices
    C. M. Anish, Archana Jadhav, Harshal N Datir, G. S. Mate, Anorgul Ashirova, Asha Rawat
    Journal of Discrete Mathematical Sciences and Cryptography, 2026
    As the number of IoT and edge devices develops swiftly, security solutions need to be both light and powerful. This study suggests using Elliptic Curve Cryptography (ECC) approaches that are supported by AI and operate best in small places. The proposed method enhance the speed of key generation, encryption, and interpreting while maintaining high ranges of safety by using AI-based optimization techniques. As compared to conventional ECC techniques, the effects of the experiments display big modifications in processing speed and less use of assets. This works allows protecting the technology of internet of things (IoT) structures with energy-saving encryption methods that use AI to enhance them.
  • Interference minimization in visible light communication systems using LSTM-based predictive resource allocation
    Dipali Himmatrao Patil, Gitanjali S. Mate, Aparna Tiwari, Seema Kedar, Archana Jadhav
    Journal of Optical Communications, 2026
    Visible light communication (VLC) has emerged as a promising technology for high-speed wireless access in indoor and vehicular environments. However, dense deployment of light-emitting diodes (LEDs) leads to severe co-channel interference, which degrades signal quality and system throughput. This paper proposes a Long Short-Term Memory (LSTM)-based interference prediction and mitigation framework for multiuser VLC networks. The temporal correlation of user mobility and channel variations is exploited using LSTM to forecast future interference levels and dynamically allocate transmit power and bandwidth. A mathematical model of the VLC channel, interference, and signal-to-interference-plus-noise ratio (SINR) is developed, and the optimization problem is formulated to minimize aggregate interference while satisfying quality-of-service constraints. Simulation results demonstrate that the proposed LSTM-based scheme significantly improves SINR, reduces bit error rate, and enhances throughput compared to conventional static and heuristic allocation methods. At a transmit power of 1 W, the throughput under interference is 114 Mbps, while the interference-free benchmark achieves 131 Mbps. The proposed LSTM-assisted framework restores throughput to 128 Mbps, closely approaching ideal conditions. These results confirm the effectiveness of the proposed predictive interference mitigation strategy for next-generation VLC systems.
  • Deep learning based bird sound classification using customized convolutional neural networks
    Deepak Mane, Pravin Kumar Bhoyar, Govinda B. Sambare, Gitanjali Mate, Dipali Patil, Archana Jadhav, Deepak R. More
    Communications in Statistics Case Studies Data Analysis and Applications, 2026
    The classification of sounds produced by birds is very helpful in ecological monitoring, research on biodiversity, and conservation activities. It can be quite difficult to recognize bird species by their calls, especially in places with many overlapping sounds or noise. This paper presents an approach for automatically classifying bird sounds with deep learning using customized Convolutional Neural Networks (CNNs). The method extracts MFCCs to capture important discriminative features from the Xeno-Canto dataset, which consists of more than 3000 audio files from 114 bird species. Three Conv1D blocks with batch normalization, max-pooling, and dense layers process these features, producing a SoftMax output of 114 units. The data is pre-processed with optimized pipelines in TensorFlow, including caching, shuffling, and prefetching, which improves model performance as well as the time taken to train the model. With the proposed approach, the new model based on CNN reached an accuracy of 93.4%, which is a significant improvement than that achieved from prior methods. The proposed model is capable of automatically and accurately identifying birds by their songs, which can greatly benefit eco-biology studies, conservation, and monitoring research.
  • Electronic Health Records: A Survey
    Nihar M Ranjan, Maya P Bembde, Gitanjali S Mate, Abhishek Kumar
    Advances of Machine Learning for Knowledge Mining in Electronic Health Records, 2025
    The Electronic Health Record (EHR) has been proven to play a vital role in the healthcare system. The significant role and application of EHR in healthcare systems includes the need to improve upon medication administration, efficient delivery of healthcare services, the safety of critical patients, smooth and real time access to healthcare data, the reduction of errors in data acquisition and, most importantly, to bring down overall medical expenditure. The main goal of this chapter is to review the current aspects and trends in the applications of EHR and its role in the healthcare system. In the healthcare system EHR has been very useful in different ways, ranging from administrative functions, critical care applications, and historical research to financial applications. EHR is not just a transition from paper based medical record to the electronic form, but it facilitates important clinical functions like the integrated view of patient data and information, knowledge access, integrated communication, critical decision support and practitioners' data entry.
  • Semantic interpretation of visible light communication traffic signals for autonomous driving
    Gitanjali S. Mate, Aparna Tiwari, Seema Kedar, Archana Jadhav, Dipali Himmatrao Patil
    Journal of Optical Communications, 2025
    Visible light communication (VLC) has emerged as a promising technology to enable high-speed, secure, and interference-free communication in intelligent transportation systems. This paper presents a novel framework for the semantic interpretation of VLC-based traffic signals to enhance the perception and decision-making capabilities of autonomous vehicles. By embedding semantic information – such as traffic states, warnings, and control commands – into modulated light signals emitted by traffic infrastructure, the proposed system allows autonomous vehicles to receive and interpret critical road information in real time. The framework integrates signal decoding, temporal synchronization, and semantic parsing to extract actionable insights from received optical signals. A deep learning-based classifier is used to map decoded messages to high-level driving decisions under varying ambient lighting and environmental conditions. Extensive simulations demonstrate the system’s robustness, achieving over 95 % accuracy in semantic message recognition and maintaining reliable communication at distances up to 30 m in outdoor conditions. This work highlights the potential of VLC as a dual-purpose medium for both illumination and intelligent traffic signalling, providing a scalable solution for enhancing situational awareness in autonomous driving.
  • Visible light communication for vehicle-to-vehicle systems: a deep neural network-based signal detection framework
    Archana Jadhav, Dipali Himmatrao Patil, Gitanjali S. Mate, Aparna Tiwari, Seema Kedar
    Journal of Optical Communications, 2025
    Visible light communication (VLC) is emerging as a promising alternative to conventional radio frequency-based vehicle-to-vehicle (V2V) communication due to its high data rate, immunity to electromagnetic interference, and use of energy-efficient LED-based vehicular lighting systems. However, signal detection in dynamic V2V-VLC environments remains a significant challenge due to factors such as high mobility, channel fading, ambient light interference, and misalignment between transmitter and receiver. This paper proposes a robust deep neural network (DNN) architecture specifically designed for accurate and reliable signal detection in V2V-VLC systems. Through extensive simulations and experimental evaluations under varying vehicular conditions, our framework achieves superior detection accuracy of 99.8 % at a distance of 1 m and 98.4 % at 5 m while exhibiting greater resilience compared to traditional signal processing methods. The research aims to enhance communication reliability in intelligent transportation systems, paving the way for safer and more efficient autonomous driving environments.
  • Skin Cancer Detection using ResNet50 and VGG16: A Deep Learning Approach
    16th International Conference on Advances in Computing Control and Telecommunication Technologies Act 2025, 2025
  • "CardioTrackGuard": A Review on Machine Learning-Based Smart Wearable System for Cardiac Arrest Monitoring
    Shweta Dhumal, Dipali Patil, Nakul Firodiya, Gauri Talokar, Vaishnavi Salunkhe, G.S. Mate
    2025 2nd International Conference on Integration of Computational Intelligent System Icicis 2025, 2025
    A new version of smart wearable system for individual use presents itself while delivering a complete assessment of contemporary cardiac arrest tracking systems. The proposed system implements hybrid computing with machine literacy capabilities to provide immediate cardiac arrest detection and faster interventions by substituting slower cloud-processed mobile systems. On-device data processing takes place exclusively on the wearable device or the ESP32 and Jetson Nano and TinyML edge computing platforms because the system operates independently. The system delivers practical emergency applications because it improves data collection speed and minimizes internet dependency combined with superior energy performance through its independent operation. The paper presents both a description of the system components and decision framework while exploring present techniques alongside innovative technologies and health detectors. Explaining that immediate medical response remains vital while the investigation shows that automated anomaly detection operated by machines would boost cardiac arrest survival rates. The research utilizes Smart Wearable System technology to monitor cardiac arrests in real-time through Hybrid Computing with access to a mobile free solution.
  • Smart E-Learning: Emotion Recognition Using VGG-16 and BiLSTM for Adaptive Learning
    Ashlesh D Rathod, Archana Jadhav, Suraj Shelke, Satyajeet Labade, Vinay Kale, Gitanjali Mate
    2nd International Conference on Research Methodologies in Knowledge Management Artificial Intelligence and Telecommunication Engineering Rmkmate 2025, 2025
  • A Framework for Automated Decision Making and Predictive Options Trading Driven by Machine Learning
    16th International Conference on Advances in Computing Control and Telecommunication Technologies Act 2025, 2025
  • Machine Learning Analysis for Options Trading a Review
    G. S. Mate, D. H. Patil, Aditya Wani, Abhishekh Dhas, Prathamesh Borade, Dnyaneshwari Shinde
    Lecture Notes in Networks and Systems, 2025
  • Application of Gaussian Process Regression for Accurate Forecasting of Renewable Energy Outputs
    Nupoor Raundal, Gitanjali Mate, Yash Nemade, Nikhil Gadhave, Ayush Pavnekar, Dipali Patil
    2025 International Conference on Computing Technologies Icoct 2025, 2025
  • Preface
    Chhaya S. Gosavi, Nuzhat Faiz Shaikh, Sandhya Arora
    Artificial Intelligence Machine Learning and User Interface Design, 2024
  • Artificial intelligence, machine learning and user interface design
    Artificial Intelligence Machine Learning and User Interface Design, 2024
  • NLP Based Automated Text Summarization and Translation: A Comprehensive Analysis
    Nikhil Zade, Gitanjali Mate, Kamal Kishor, Nishant Rane, Manmath Jete
    2nd International Conference on Sustainable Computing and Smart Systems Icscss 2024 Proceedings, 2024
  • Demystifying Liver Disease Prediction: The Role of PSO Algorithm
    Gitanjali S Mate, Pratik Sutar, Vinayak Mhaske, Omkar Jaybhaye, Yash Wagh
    2024 Opju International Technology Conference on Smart Computing for Innovation and Advancement in Industry 4 0 Otcon 2024, 2024
  • Anticipating the 'Green Wave' with Data: Enhancing the Approach Towards Load Forecasting of Renewable Energy Sources in India
    Nupoor Raundal, Gitanjali Mate, Nikhil Gadhave, Ayush Pavnekar, Yash Nemade
    2024 International Conference on Artificial Intelligence and Quantum Computation Based Sensor Applications Icaiqsa 2024 Proceedings, 2024
  • Credit Card Fraud Detection by Using Ensemble Method of Machine Learning
    Nihar Ranjan, G. S. Mate, A. J. Jadhav, D. H. Patil, A. N. Banubakode
    Lecture Notes in Networks and Systems, 2024
  • Assessing Knee Osteoarthritis Severity: A Deep Learning Approach with Enhanced ResNet152
    Gitanjali Mate, Madhavi Mahajan, Pragati Mahajan, Prajwal Janbandhu, Rutuja Shinde, Archana Jadhav
    Raics IEEE Recent Advances in Intelligent Computational Systems, 2024
  • Transact Safe: A Machine Learning Shield against Online Fraud
    15th International Conference on Advances in Computing Control and Telecommunication Technologies Act 2024, 2024
  • Innovations in Safeguarding Online Financial Transactions using Ensemble Learning
    Sameer Pathan, Archana Jadhav, Md Suhel Shaikh, Ajit Huke, Gitanjali Mate, Chandan Prasad
    2024 Opju International Technology Conference on Smart Computing for Innovation and Advancement in Industry 4 0 Otcon 2024, 2024
  • A Review: Smart Wristwear for Alzheimer Patients with an Advanced Tracking System
    Rutuja Javheri, Dipali Patil, Aarti Kamble, Arpita Yadav, Prathmesh Kolhe, G.S. Mate
    2024 IEEE Region 10 Symposium Tensymp 2024, 2024
  • A SENS Score of Rheumatoid Arthritis Detection Using Customized Convolutional Neural Network
    G. S. Mate, A. N. Paithane, N. M. Ranjan
    Lecture Notes in Networks and Systems, 2023
  • Recognition of Varities of Rice Using Deep Learning Technologies
    Hritika Jadhav, Rahul Sanap, Anuradha Kotgire, Sanchi Kamble, Gitanjali Mate
    Communications in Computer and Information Science, 2023
  • Recognition of the Varieties of Rice using CNN
    14th International Conference on Advances in Computing Control and Telecommunication Technologies Act 2023, 2023
  • Inflated 3D Video Summarization: A Comprehensive Review
    Nihar M. Ranjan, G.S. Mate, Dipali Himmatrao Patil, A.J. Jadhav, S.A. Adhav, R.T. Umbare
    3rd International Conference on Innovative Mechanisms for Industry Applications Icimia 2023 Proceedings, 2023
  • Applications of Human-Computer Interaction for Improving ERP Usability in Education Systems
    Human Computer Interaction and Beyond Advances Towards Smart and Interconnected Environments Part II, 2022
  • Erratum: An efficient CNN for hand x-ray classification of rheumatoid arthritis (Journal of Healthcare Engineering (2021) 2021 (6712785) DOI: 10.1155/2021/6712785)
    Gitanjali S. Mate, Abdul K. Kureshi, Bhupesh Kumar Singh
    Journal of Healthcare Engineering, 2021
  • Applications of HCI in Health Care for Diagnosis of Rheumatoid Arthritis
    Human Computer Interaction and Beyond Advances Towards Smart and Interconnected Environments Part I, 2021
  • An Efficient CNN for Hand X-Ray Classification of Rheumatoid Arthritis
    Gitanjali S. Mate, Abdul K. Kureshi, Bhupesh Kumar Singh
    Journal of Healthcare Engineering, 2021
  • Improving Efficiency of Similarity of Document Network Using Bisect K-Means
    Pradnya Kadam, G.S. Mate
    2017 International Conference on Computing Communication Control and Automation Iccubea 2017, 2017

RECENT SCHOLAR PUBLICATIONS

  • Enhanced speech emotion detection via Signed Cumulative Distribution Transform and Progressive Graph Convolutional Networks
    S Kedar, P Thakre, A Jadhav, GS Mate, DH Patil
    International Journal of Speech Technology 29 (1), 19 , 2026
    2026
  • Next-Gen Chest Cancer Detection using AI Techniques.
    S Yadav, D Bagul, S Ardhapure, P Awchar, RT Umbare, GS Mate
    Grenze International Journal of Engineering & Technology (GIJET) 12 (Part2 … , 2026
    2026
  • Deep learning based bird sound classification using customized convolutional neural networks
    D Mane, PK Bhoyar, GB Sambare, G Mate, D Patil, A Jadhav, DR More
    Communications in Statistics: Case Studies, Data Analysis and Applications, 1-24 , 2026
    2026
  • Semantic interpretation of visible light communication traffic signals for autonomous driving
    GS Mate, A Tiwari, S Kedar, A Jadhav, DH Patil
    Journal of Optical Communications , 2025
    2025
  • Visible light communication for vehicle-to-vehicle systems: a deep neural network-based signal detection framework
    A Jadhav, DH Patil, GS Mate, A Tiwari, S Kedar
    Journal of Optical Communications , 2025
    2025
    Citations: 2
  • “CardioTrackGuard”: A Review on Machine Learning-Based Smart Wearable System for Cardiac Arrest Monitoring
    S Dhumal, D Patil, N Firodiya, G Talokar, V Salunkhe, GS Mate
    2025 2nd International Conference on Integration of Computational … , 2025
    2025
  • Machine Learning Analysis for Options
    GS Mate, DH Patil, A Wani, A Dhas, P Borade
    Advances in Data-driven Computing and Intelligent Systems: Selected Papers … , 2025
    2025
  • Application of Gaussian Process Regression for Accurate Forecasting of Renewable Energy Outputs
    N Raundal, G Mate, Y Nemade, N Gadhave, A Pavnekar, D Patil
    2025 International Conference on Computing Technologies (ICOCT), 1-6 , 2025
    2025
  • Smart E-Learning: Emotion Recognition Using VGG-16 and BiLSTM for Adaptive Learning
    AD Rathod, A Jadhav, S Shelke, S Labade, V Kale, G Mate
    2025 2nd International Conference on Research Methodologies in Knowledge … , 2025
    2025
    Citations: 1
  • Electronic Health Records: A Survey
    NM Ranjan, MP Bembde, GS Mate, A Kumar
    Advances of Machine Learning for Knowledge Mining in Electronic Health … , 2025
    2025
  • 12 Electronic Health
    NM Ranjan, MS Bembde, GS Mate, A Kumar
    Advances of Machine Learning for Knowledge Mining in Electronic Health … , 2025
    2025
  • Anticipating the ‘Green Wave’with Data: Enhancing the Approach Towards Load Forecasting of Renewable Energy Sources in India
    N Raundal, G Mate, N Gadhave, A Pavnekar, Y Nemade
    2024 International Conference on Artificial Intelligence and Quantum … , 2024
    2024
  • A Review: Smart Wristwear for Alzheimer Patients with an Advanced Tracking System
    R Javheri, D Patil, A Kamble, A Yadav, P Kolhe, GS Mate
    2024 IEEE Region 10 Symposium (TENSYMP), 1-6 , 2024
    2024
    Citations: 1
  • Machine Learning Analysis for Options Trading a Review
    GS Mate, DH Patil, A Wani, A Dhas, P Borade, D Shinde
    International Conference on Advances in Data-driven Computing and … , 2024
    2024
  • NLP based automated text summarization and translation: a comprehensive analysis
    N Zade, G Mate, K Kishor, N Rane, M Jete
    2024 2nd International Conference on Sustainable Computing and Smart Systems … , 2024
    2024
    Citations: 13
  • Transact Safe: A Machine Learning Shield against Online Fraud.
    A Huke, A Jadhav, MS Shaikh, S Pathan, GS Mate, C Prasad
    Grenze International Journal of Engineering & Technology (GIJET) 10 , 2024
    2024
  • Innovations in Safeguarding Online Financial Transactions using Ensemble Learning
    S Pathan, A Jadhav, MS Shaikh, A Huke, G Mate, C Prasad
    2024 OPJU International Technology Conference (OTCON) on Smart Computing for … , 2024
    2024
    Citations: 1
  • Demystifying Liver Disease Prediction: The Role of PSO Algorithm
    GS Mate, P Sutar, V Mhaske, O Jaybhaye, Y Wagh
    2024 OPJU International Technology Conference (OTCON) on Smart Computing for … , 2024
    2024
  • Assessing knee osteoarthritis severity: A deep learning approach with enhanced ResNet152
    G Mate, M Mahajan, P Mahajan, P Janbandhu, R Shinde, A Jadhav
    2024 IEEE Recent Advances in Intelligent Computational Systems (RAICS), 1-7 , 2024
    2024
    Citations: 4
  • Artificial Intelligence, Machine Learning and User Interface Design
    A Banubakode, N Dhotre, Sunita,Chaya, Gosavi,Gitanjali, Mate,Shaikh, ...
    2024
    Citations: 2

MOST CITED SCHOLAR PUBLICATIONS

  • An Efficient CNN for Hand X-Ray Classification of Rheumatoid Arthritis
    GS Mate, AK Kureshi, BK Singh
    2021
    Citations: 39
  • Detection of Parkinson's Disease using Machine Learning Algorithms and Handwriting Analysis
    NM Ranjan, G Mate, M Bembde
    Journal of Data Mining and Management (e-ISSN: 2456-9437) 8 (1), 21-29 , 2023
    2023
    Citations: 24
  • Stock prediction through news sentiment analysis
    GS Mate, A Siddhant, K Rutuja, M Maitreyi
    Journal of Architecture & Technology 11 (8), 36-40 , 2019
    2019
    Citations: 14
  • NLP based automated text summarization and translation: a comprehensive analysis
    N Zade, G Mate, K Kishor, N Rane, M Jete
    2024 2nd International Conference on Sustainable Computing and Smart Systems … , 2024
    2024
    Citations: 13
  • Designing User Interfaces with a Data Science Approach
    AN Banubakode, MGS Gosavi, Chhaya Santosh
    IGI Global , 2022
    2022
    Citations: 7
  • Automatic prediction of rheumatoid arthritis using CNN
    GS Mate, MS Patil, MS Chavan, MS Harshada
    International Journal of Management Technology and Engineering 3 (9), 424-429 , 2019
    2019
    Citations: 6
  • An Efficient CNN for Hand X-Ray Classification of Rheumatoid Arthritis
    M G.S., AK Kureshi
    Microprocessors and Microsystems , 2023
    2023
    Citations: 5
  • Assessing knee osteoarthritis severity: A deep learning approach with enhanced ResNet152
    G Mate, M Mahajan, P Mahajan, P Janbandhu, R Shinde, A Jadhav
    2024 IEEE Recent Advances in Intelligent Computational Systems (RAICS), 1-7 , 2024
    2024
    Citations: 4
  • Human-Computer Interaction and Beyond: Advances Towards Smart and Interconnected Environments (Part II)
    P Mate G.S. Banubakode
    Bentham Science Publishers , 2022
    2022
    Citations: 4
  • Mood detection with chatbot using AI-desktop partner
    GM Mate, N Wadekar, R Chavan, T Rajput, S Pawar, S Rscoe
    IETE International Conference on Acadamic Reseach in Engineerng and … , 2017
    2017
    Citations: 4
  • Iot transaction security
    G Jogdand, S Kadam, K Patil, G Mate
    J. Adv. Sch. Res. Allied Educ 15, 711-716 , 2018
    2018
    Citations: 3
  • Improving efficiency of similarity of document network using bisect K-means
    P Kadam, GS Mate
    2017 International Conference on Computing, Communication, Control and … , 2017
    2017
    Citations: 3
  • Cued Click Point (Ccp) Algorithm for Graphical Password To Authenticate Shoulder Surfing Resistance
    S Sharma, GS Mate, M Pawar, S Patil, S Gole
    International Conference on Academic Research in Engineering and Management … , 2017
    2017
    Citations: 3
  • A survey paper on authentication for shoulder surfing resistance for graphical password using cued click point (CCP)
    M Pawar, GS Mate, S Sharma, S Gole, S Patil
    International Journal of Advanced Research in Computer and Communication … , 2017
    2017
    Citations: 3
  • RIPD: Route Information and Pothole Detection
    S Garg, PGS Mate, R Das, S Tiple, A Panicker
    International Journal of Advanced Research in Computer and Communication … , 2015
    2015
    Citations: 3
  • Visible light communication for vehicle-to-vehicle systems: a deep neural network-based signal detection framework
    A Jadhav, DH Patil, GS Mate, A Tiwari, S Kedar
    Journal of Optical Communications , 2025
    2025
    Citations: 2
  • Artificial Intelligence, Machine Learning and User Interface Design
    A Banubakode, N Dhotre, Sunita,Chaya, Gosavi,Gitanjali, Mate,Shaikh, ...
    2024
    Citations: 2
  • Credit Card Fraud Detection by Using Ensemble Method of Machine Learning
    N Ranjan, GS Mate, AJ Jadhav, DH Patil, AN Banubakode
    Advances in Data-Driven Computing and Intelligent Systems: Selected Papers … , 2024
    2024
    Citations: 2
  • A Survey Paper on Authentication for Shoulder Surfing Resistance for Graphical Password Using Cued Click Point (CCP)
    GS Mate, S Soni, P Snehal
    International Journal of Advanced Research in Computer and Communication … , 2017
    2017
    Citations: 2
  • Smart E-Learning: Emotion Recognition Using VGG-16 and BiLSTM for Adaptive Learning
    AD Rathod, A Jadhav, S Shelke, S Labade, V Kale, G Mate
    2025 2nd International Conference on Research Methodologies in Knowledge … , 2025
    2025
    Citations: 1