Bangole Narendra Kumar Rao

Scopus Publications

Predicting student satisfaction in metaverse platform using deep learning
Shaik Shameen Taz, B.Narendra Kumar Rao
Knowledge Based Systems, 2026
Enhanced Skin Disease Classification Through Convolutional Neural Networks: A Performance Advantage Study
Subha T, Narendra Kumar Rao, Ranjana R, Indurekaa S R
Ingenierie Des Systemes D Information, 2026
REAL-TIME ARTIFICIAL INTELLIGENCE (AI): Key Motivations, Technologies, Platforms, and Use Cases
Pethuru Raj, B. Sundaravadivazhagan, V. Kavitha, B. Narendra Kumar Rao, Hannah Vijaykumar
Real Time Artificial Intelligence AI Key Motivations Technologies Platforms and Use Cases, 2026
Predictive Analytics for Employee Retention Using Random Forest Approach
K. Srujan Raju, Adaga Sri Sai Sankar, Chatakondu Suryanarayana, K. S. Kannan, K. Reddy Madhavi, B. Narendra Kumar Rao
Lecture Notes in Networks and Systems, 2026
Deepfake Face Detection System for Differentiating Real and Authentic Images
B. Narendra Kumar Rao
AI Driven Approaches for Fully Automated Smart Engineering, 2025
The application of deepfake technology poses a significant threat to the authenticity of multimedia content, as it enables the creation of remarkably realistic yet altered photographs and videos. The present study introduces an innovative approach to identify deepfakes through the utilization of advanced deep learning methodologies. The proposed model employs convolutional neural networks (CNNs) and recurrent neural networks (RNNs) to analyze multimedia content for minute patterns that indicate tampering to detect the fake and authentic images in media. By being exposed to a diverse dataset comprising authentic and altered visual content, the model gains the capability to discern between legitimate and profoundly erroneous information. The performance of the model is evaluated utilizing a range of comprehensive assessment metrics, including accuracy, precision, and recall. The research contributes to ongoing efforts to combat the dissemination of profoundly false information by enhancing the ability to identify and mitigate the potential risks associated with deceptive multimedia.
Food image recognition and calorie estimation
B. Narendra Kumar Rao, Nidyanand Yuvaraj Singh, P. Sathvik Chowdari, Mallela Nikhil Kumar Reddy, Murthy Chetty Muni Sreenivas
Optimizing Smart and Sustainable Agriculture for Sustainability, 2025
Given the escalating health challenges associated with obesity, there is a heightened focus on adopting healthier eating habits. With 2.8 million people succumbing to overweight-related issues annually, individuals are increasingly prioritizing food choices to prevent conditions like high blood pressure, diabetes, and heart problems. A key element in any dietary plan is vigilant calorie monitoring. To facilitate this, there is a proposal to leverage deep learning (DL) technology for calorie calculation based on user-captured food images. The process involves identifying the food category and employing DL algorithms to predict calorie content. Machine learning techniques, including convolutional neural networks, play a pivotal role in image recognition and food classification. The system incorporates segmentation and imaging parameters to enhance accurate food image analysis. Ultimately, this system empowers individuals to make informed decisions about their daily calorie intake, fostering awareness of both nutritional and cost aspects of the food they consume.
Detection of partially occluded area in face image using U-Net model
Cherapanamjeri Jyothsna, Bangole Narendra Kumar Rao
Iaes International Journal of Artificial Intelligence, 2025
<span lang="EN-US">Occluded face recognition is important task in computer vision. To complete the occluded face recognition efficiently, first we need to identify the occluded region in face. Identifying the occluded region in face is a challenging task in computer vision. One case of face occlusion is nothing but wearing masks, sunglasses, and scarves. Another case of face occlusion is face is hiding the other objects like books, things, or other faces. In our research, identifying the occluded area which is corona virus disease of 2019 (COVID-19) masked area in face and generate segmentation map. In semantic segmentation, deep learning-based techniques have demonstrated promising outcomes. We have employed one of the deep learning-based<br />U-Net models to generate a binary segmentation map on masked region of a human face. It achieves reliable performance and reducing network complexity. We train our model on MaskedFace-CelebA dataset and accuracy is 97.7%. Results from experiments demonstrate that, in comparison to the most advanced semantic segmentation models, our approach achieves a promising compromise between segmentation accuracy and computing efficiency.</span>
EEG Based Sentiment Classification Using XGBoost: A Machine Learning Approach for Emotion Recognition
G. Sailaja, B. Narendra Kumar Rao
Journal Europeen Des Systemes Automatises, 2025
Child Mortality Prediction Using Machine Learning Techniques
B. Narendra Kumar Rao
Ethics Justice and Governance in the Age of AI and Digital Societies, 2025
This project explores the application of machine learning techniques to predict child mortality by analyzing a dataset of 2,126 cardiotocogram (CTG) measurements, which detail fetal heart rate and uterine contraction patterns and have been meticulously classified by expert obstetricians. The study employs and compares various machine learning models, including logistic regression, decision trees, and neural networks, to assess their efficacy in identifying high-risk pregnancies. By leveraging these advanced predictive models, the research aims to enhance the accuracy of risk assessments and uncover critical patterns in fetal health data that may not be detectable through conventional methods. The ultimate goal is to support early interventions and improve child survival rates through data-driven decision-making in healthcare. This project has significant implications for enhancing predictive modeling and risk assessment in obstetrics, contributing to more effective and personalized maternal and child health care strategies.
Improving Cervical Cancer Recurrence Prediction Through Multi-Source Data Integration and Advanced Deep Learning Approaches
Prathap Sathyavedu, B.Narendra Kumar Rao
3rd IEEE International Conference on Industrial Electronics Developments and Applications Icidea 2025, 2025
Cervical cancer recurrence prediction is a very crucial point in treatment because needing as much accuracy and speed as possible calls for better patient care. This research work presents the design of a high-performance predictive model that integrates multi-modal clinical data, such as imaging, genetic profiles, and health records of patients, to enhance accuracy in predicting recurrence. This can enable the capture of intricate factors of recurrence risk with the help of this kind of multimodal data integration. Deep learning techniques like convolutional neural networks and transformers are applied to each independent data source, with this model emphasizing attention mechanisms for interpretability that will inspire greater clinical trust and usability. In contrast to many conventional approaches that often use a single data source, this integrated methodology overcomes the critical limitations of using a broader spectrum of clinical inputs. It is further strengthened by data augmentation and generation of synthetic data, overcoming problems of data imbalance. Extensive validation on various datasets yielded a predictive accuracy of 95.7%, demonstrating its high performance. This holistic approach presented them with a valid and accurate method for predicting cervical cancer recurrence, thus equipping the clinicians with the necessary insight into informed decision-making that could lead to improved patient care and outcomes.
The metaverse as an educational tool: Enhancing learning with blockchain technology
B. Narendra Kumar Rao, Shaik Shameen Taz
Engineering the Metaverse Enabling Technologies Platforms and Use Cases, 2025
Harnessing Deep Learning Techniques for the Removal of Occlusion in Face Image
Jyothsna Cherapanamjeri, Narendra Kumar Rao Bangole
Advances in Artificial Intelligence and Machine Learning, 2025
Enhanced Brain Tumor Classification through an AI-Integrated Multi-Modal Imaging Approach
Nagolu Divya, B Narendra Kumar Rao
Proceedings of the 3rd International Conference on Intelligent and Innovative Technologies in Computing Electrical and Electronics Iitcee 2025, 2025
Harnessing deep learning for the early detection of COVID-19 using chest X-rays
B. Narendra Kumar Rao, B. Bhaskar Kumar Rao, Nagendra Panini Challa
Big Data Analytics and Intelligent Applications for Smart and Secure Healthcare Services, 2025
IoT, AI, and metaverse in smart healthcare systems: A review of recent advances and future trends
B. Narendra Kumar Rao, N. Bala Krishna, Chinthapatla Pranay Varna
Engineering the Metaverse Enabling Technologies Platforms and Use Cases, 2025
Application of metaverse in regenerative medicine: Applications and challenges
R. Ranjana, R.K. Sahana, B. Narendra Kumar Rao
Engineering the Metaverse Enabling Technologies Platforms and Use Cases, 2025
Automatic Number Plate Recognition for Motorcyclists Riding Without Helmet
B. Narendra Kumar Rao, Vemula Shalini, Kullai Balaji, Ponthagiri Venkata Siva Kalyan
Lecture Notes in Intelligent Transportation and Infrastructure, 2025
Metaverse for Indian palm leaf manuscripts
Basaraboyina Yohoshiva, Nagendra Panini Challa, Narendra Kumar Rao, Beebi Naseeba, Venkata Sasi Deepthi Ch
Engineering the Metaverse Enabling Technologies Platforms and Use Cases, 2025
Diabetic Prediction Using Deep Learning Techniques
B. Narendra Kumar Rao, Nagendra Panini Challa, S. Sreenivasa Chakravarthi, R. Ranjana, B. Bhaskar Kumar Rao
Lecture Notes in Networks and Systems, 2025
Crafting Shopping Experiences Using Artificial Intelligence
B. Narendra Kumar Rao, Sankara Rudra Abhiram, M. Mohan Reddy, V. Shireen, P. Poojitha
Synergy of AI and Fintech in the Digital Gig Economy, 2025
Gesture Assist: A Companion for Elderly with Gesture and Emotion Recognition
B. Narendra Kumar Rao, Nagendra Panini Challa, S. Sreenivasa Chakravarthi, J. Vellingiri, R. Ranjana, B. Bhaskar Kumar Rao
Lecture Notes in Networks and Systems, 2025
Auto Proctoring on Tab Switch Monitoring for Online Examinations in Scalable Web Interface Design
Md. Mohammad Shareef, L. N. C. K. Prakash, Madduri Deepika, K. Sandhya, B. Narendra Kumar Rao, K. Reddy Madhavi
Lecture Notes in Networks and Systems, 2025
Enhancing Event Organization Efficiency Through Intelligent Chatbot: A Study on Automated Assistance and Engagement
Avala Raji Reddy, K. R. Bhavya, M. Srilekha, Narendhar Mulugu, K. Sandhya, B. Narendra Kumar Rao
Lecture Notes in Networks and Systems, 2025
Unmasking Sarcasm: Exploring Machine Learning Approaches for Sarcasm Detection and Comparative Evaluation
Abbaraju Sai Sathwik, B. Narendra Kumar Rao, Bheri Saiteja, A. Koteswara Rao, K. Reddy Madhavi, S. Bhaskar Nikhil
Lecture Notes in Networks and Systems, 2025
Metaverse for heart illness prediction and analysis
Bollapalli Althaph, Nagendra Panini Challa, Narendra Kumar Rao, Kamepalli SL Prasanna, Nagaraju Jajam, Venkata Sasi Deepthi Ch, Beebi Naseeba
Engineering the Metaverse Enabling Technologies Platforms and Use Cases, 2025
Engineering the metaverse: Enabling technologies, platforms and use cases
Kumar, Pethuru Raj Prasanna, Sharma, D. P., Saini, Kavita, Rao, B. Narendra Kumar, Kosuri, Harshavardhan, et al.
Engineering the Metaverse Enabling Technologies Platforms and Use Cases, 2025
Machine learning for real-time stress analysis in IT teams
N. Balakrishna, Khwaja Moinuddin Basha S., T. Rajasree, P. Vinitha, C. Gnanaprakash, K. Ghamya, Narendra Kumar Rao Bangole
Impact of Corporate Social Responsibility on Employee Wellbeing, 2024
Recommendation System for E-Commerce Using Collaborative Filtering
Preeti Patil, Sandeep Uddhavrao Kadam, E.R. Aruna, Amar More, Balajee R. M., B. Narendra Kumar Rao
Journal Europeen Des Systemes Automatises, 2024
A machine learning-based crop diseases detection and management system
Narendra Kumar Rao Bangole
Advanced Computational Methods for Agri Business Sustainability, 2024
Human migration analysis using machine learning
Narendra Kumar Rao Bangole, Lingam Thanvitha, T. Benazir Suraiya, Y. N. V. Shashank, N. Loka Harshith
Media Representation of Migrants and Refugees, 2024
Making healthcare decisions: An evolution
Venkata Tulasiramu Ponnada, Venkata Tulasikrishna Ponnada, Narendra Kumar Rao B., Rama Krishna Raju Sammeta, Hymavathi Jasti
Intelligent Decision Making Through Bio Inspired Optimization, 2024
Brain interaction assessment using EEG source localization: SLORETA
B. Narendra Kumar Rao, G. Sailaja
Medical Robotics and AI Assisted Diagnostics for A High Tech Healthcare Industry, 2024
Bone fracture detection and classification using deep learning techniques
B. Narendra Kumar Rao, B. Pranitha, B. Kushal Reddy, D. Varsha, N. Nithin Reddy
Driving Smart Medical Diagnosis Through AI Powered Technologies and Applications, 2024
Enabling smart farming through edge artificial intelligence (AI)
J. Avanija, C. Rajyalakshmi, K. Reddy Madhavi, B. Narendra Kumar Rao
Agriculture and Aquaculture Applications of Biosensors and Bioelectronics, 2024
Enhancing smart agriculture applications utilizing deep learning models and computer vision techniques
K. Srujan Raju, K. Suneetha, K. Reddy Madhavi, Kondra Pranitha, J. Avanija, et al.
Agriculture and Aquaculture Applications of Biosensors and Bioelectronics, 2024
Factors Influencing Mental Health and the Role of Artificial Intelligence (AI) in the Era of Climate Change
G. Sailaja, Rao B. Kumar Narendra
AI and Iot Technology and Applications for Smart Healthcare Systems, 2024
Deep Learning Approaches for Occlusion Removal in Medical Images
Kaluva Jaya Deepthi, B. Narendra Kumar Rao
Proceedings of 2024 2nd International Conference on Recent Trends in Microelectronics Automation Computing and Communications Systems Exploration and Blend of Emerging Technologies for Future Innovation Icmacc 2024, 2024
Detection of Partially Occluded Area in Images Using Image Segmentation Technique
Jyothsna Cherapanamjeri, B. Narendra Kumar Rao
Lecture Notes in Networks and Systems, 2024
Building Tomorrow: Navigating Sustainable Construction with Artificial Intelligence
Revathi Pasupuleti, Eswara Reddy Orekanti, B. Narendra Kumar Rao
Proceedings 2024 International Conference on Social and Sustainable Innovations in Technology and Engineering Sasi ITE 2024, 2024
Crop Disease Analysis and Detection using GoogleNet Model
Bollapalli Althaph, Nagendra Panini Challa, Beebi Naseeba, Narendra Kumar Rao
Proceedings of the 18th Indiacom 2024 11th International Conference on Computing for Sustainable Global Development Indiacom 2024, 2024
Crafting Shopping Experiences Using Artificial Intelligence
B. Narendra Kumar Rao, Sankara Rudra Abhiram, M. Mohan Reddy, V. Shireen, P. Poojitha
Synergy of AI and Fintech in the Digital Gig Economy, 2024
Crop Growth Prediction using Ensemble KNN-LR Model
Attaluri Harshitha, Beebi Naseeba, Narendra Kumar Rao, Abbaraju Sai Sathwik, Nagendra Panini Challa
Eai Endorsed Transactions on Internet of Things, 2024
TRENDS AND FUTURE RESEARCH DIRECTIONS OF INNOVATIONS IN COMPUTATIONAL INTELLIGENCE, BIG DATA ANALYTICS, AND INTERNET OF THINGS
Innovations in Computational Intelligence Big Data Analytics and Internet of Things, 2024
Playing rock-paper-scissors using ai through openCV
Narendra Kumar Rao Bangole, S. Ranjana
Software Principles of Design for Data Modeling, 2023
Game playing (2048) using deep neural networks
Narendra Kumar Rao Bangole, R. B. Moulya, R. Pranthi, Sreelekha Reddy, R. Namratha
Software Principles of Design for Data Modeling, 2023
A conceptual framework for addressing the information of farmers: A study on digital agriculture
Narendra Kumar Rao Bangole, G.M. Chanakya, P. Rajesh
Handbook of Research on AI Equipped Iot Applications in High Tech Agriculture, 2023
Early Alzheimer’s Disease Detection Using Deep Learning
Kokkula Lokesh, Nagendra Panini Challa, Abbaraju Sai Satwik, Jinka Chandra Kiran, Narendra Kumar Rao, Beebi Naseeba
Eai Endorsed Transactions on Pervasive Health and Technology, 2023
Hyperparameter Optimization for Transfer Learning-based Disease Detection in Cassava Plants
Kalyani G, Sai Sudheer K, Janakiramaiah B, Narendra Kumar Rao B
Journal of Scientific and Industrial Research, 2023
A wellness mobile application for smart health
B. Narendra Kumar Rao
Designing and Developing Innovative Mobile Applications, 2023
Gesture Recognition for Enhancing Human Computer Interaction
Journal of Scientific and Industrial Research, 2023
Demystifying explainable artificial intelligence (EAI)
Explainable Artificial Intelligence Xai Concepts Enabling Tools Technologies and Applications, 2023
Preface
Smart Innovation Systems and Technologies, 2023
Fine-tuning for Transfer Learning of ResNet152 for Disease Identification in Tomato Leaves
Lakshmi Ramani Burra, Janakiramaiah Bonam, Praveen Tumuluru, B. Narendra Kumar Rao
Smart Innovation Systems and Technologies, 2023
Edge Intelligence with Light Weight CNN Model for Surface Defect Detection in Manufacturing Industry
Journal of Scientific and Industrial Research, 2023
Convolutional Neural Network Model for Traffic Sign Recognition
B Narendra Kumar Rao, R Ranjana, Nagendra Panini Challa, S. Sreenivasa Chakravarthi
2023 3rd International Conference on Advance Computing and Innovative Technologies in Engineering Icacite 2023, 2023
Facial Landmarks Detection System with OpenCV Mediapipe and Python using Optical Flow (Active) Approach
Narendra Kumar Rao B, Nagendra Panini Challa, E S Phalguna Krishna, S. Sreenivasa Chakravarthi
2023 3rd International Conference on Advance Computing and Innovative Technologies in Engineering Icacite 2023, 2023
Text Recognition from Images Using Deep Learning Techniques
B. Narendra Kumar Rao, Kondra Pranitha, Ranjana Ranjana, C. V. Krishnaveni, Midhun Chakkaravarthy
Smart Innovation Systems and Technologies, 2023
Multi-layered PCM Method for Detecting Occluded Object in Secluded Remote Sensing Image
B. Narendra Kumar Rao, Apparao Kamarsu, Kanaka Durga Returi, V. Mohan, K. Reddy Madhavi
Lecture Notes in Networks and Systems, 2023
Object Sub-Categorization and Common Framework Method using Iterative AdaBoost for Rapid Detection of Multiple Objects
Journal of Scientific and Industrial Research, 2023
Machine learning and computer vision - beyond modeling, training, and algorithms
Explainable Artificial Intelligence Xai Concepts Enabling Tools Technologies and Applications, 2023
Speech Emotion Recognizer Using CNN
B. N. Kumar Rao, Rekhasree Manthu, Kovuri Praveen Kumar, G. Madhukar, K. Madhavi, Ganpat Joshi
5th IEEE International Conference on Cybernetics Cognition and Machine Learning Applications Icccmla 2023, 2023
Automated Detection of Skin Lesions Using Back Propagation Neural Network
Nagendra Panini Challa, A. Mohan, Narendra Kumar Rao, Bhaskar Kumar Rao, J. S. Shyam Mohan, B. Balaji Bhanu
Smart Innovation Systems and Technologies, 2023
Cardiac Anomaly Detection Using Machine Learning
Beebi Naseeba, A. Prem Sai Haranath, Sasi Preetham Pamarthi, S. Farook, Bir Bhanu, et al.
Lecture Notes in Networks and Systems, 2023
Sparsely Supervised Learning for Medical Image Classification on Noisy Heterogeneous Data
Thillai Manjari T, S. Sreenivasa Chakravarthi, S. Sountharrajan, B. Narendra Kumar Rao, E. Suganya, et al.
2023 3rd International Conference on Advance Computing and Innovative Technologies in Engineering Icacite 2023, 2023
Neural Networks based Object Detection Techniques in Computer Vision
Jyothsna Cherapanamjeri, B. Narendra Kumar Rao
4th International Conference on Inventive Research in Computing Applications Icirca 2022 Proceedings, 2022
Object detection techniques for real-time applications
Streaming Analytics Concepts Architectures Platforms Use Cases and Applications, 2022
Movie Recommendation System using Machine Learning
Narendra Kumar Rao, Nagendra Panini Challa, S Sreenivasa Chakravarthi, R Ranjana
4th International Conference on Inventive Research in Computing Applications Icirca 2022 Proceedings, 2022
ML Approaches to Detect Email Spam Anamoly
B Narendra Kumar Rao, P. Partheeban, Beebi Naseeba, Hemadri Prasad Raju
2022 International Conference on Data Science Agents and Artificial Intelligence Icdsaai 2022, 2022
Virtual Alphabet Recognition using Deep Convolution Neural Networks
Nagendra Panini Challa, Ranjana R, S Sreenivasa Chakravarthi, Narendra Kumar Rao
4th International Conference on Inventive Research in Computing Applications Icirca 2022 Proceedings, 2022
Grand challenges scholars program in indian context
Journal of Engineering Education Transformations, 2020
Predictive maintenance for monitoring heritage buildings and digitization of structural information
International Journal of Innovative Technology and Exploring Engineering, 2019
Block chain based implementation of electronic medical health record
International Journal of Innovative Technology and Exploring Engineering, 2019
Clustering based test suite selection for ranking of program execution sequence using improved precision in regression testing
International Journal of Innovative Technology and Exploring Engineering, 2019
An unbiased privacy sustaining approach based on SGO for distortion of data sets to shield the sensitive patterns in trading alliances
B. Janakiramaiah, G. Kalyani, Suresh Chittineni, B. Narendra Kumar Rao
Smart Innovation Systems and Technologies, 2019
Feature matching in Iris recognition system using Matlab
Imran Naguru, Narendra Kumar Rao B
International Journal on Advanced Science Engineering and Information Technology, 2017
Frequent segment clustering of test cases for test suite reduction
Wseas Transactions on Computers, 2014
Case based reasoning approach for adaptive test suite optimization
B. Narendra Kumar Rao, A. RamaMohan Reddy
2012 3rd International Conference on Computing Communication and Networking Technologies Icccnt 2012, 2012
Level dependencies of individual entities in random unit testing of structured code
B. Narendra Kumar Rao, A Rama Mohan Reddy, K Ravi
Icect 2011 2011 3rd International Conference on Electronics Computer Technology, 2011

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