IEEE

Enhancing Customer Retention: A Federated Machine Learning Framework for Banking Churn Prediction

Abstract: Customer attrition has become the significant challenge for the bank, making large volume of customers to migrate to other banks, as the banks keeps providing multiple benefits to the ...
IEEE

Forest Fire Forecasting Leveraging Modis Satellite Fire Data Using Machine Learning For Jharkhand State, India

Abstract: Forest fires pose significant environmental and economic threats, necessitating robust predictive models for better management and prevention. This study focuses on the temporal and spatial ...
IEEE

Customer Segmentation using Mini Batch K-Means Clustering Algorithm

Abstract: Today, especially in this era of data, everything is becoming more mechanized. Data is the new electricity of the globe. This knowledge may help a lot of businesses in their marketing ...
IEEE

Machine Learning Insights for Predicting Customer Behavior in Online Retail

Abstract: The research work reports a comprehensive analysis of predictive analytics of customer behavior on e-commerce based on high-end data science and artificial intelligence techniques. The ...
IEEE

3D Semantic Segmentation of Airborne & UAV LiDAR Point Clouds for Precise Tree Counting: a Machine Learning Approach

Abstract: In a world where sustainable forest management and understanding of our ecosystems have become priorities, accurately and efficiently counting trees, especially in geographically challenging ...
IEEE

Leveraging Personalized Customer Experiences in Mobile Edge Computing Through Split Learning Using Smart Data-Driven Modeling

Abstract: The rapid growth and opportunities of Mobile Edge Computing (MEC) technology have transformed smart consumer electronics like smartphones and wearable devices that produce massive and ...
IEEE

Balancing Data Imbalance in Remote Sensing Image Road Segmentation With Gradient-Guided Multi-Level Data Augmentation

Abstract: In remote sensing image segmentation, data imbalance remains a critical challenge, particularly in datasets from networks and natural scenes, increasing task complexity. Recent studies have ...
IEEE

Anomaly Detection in Sensor Data using Machine Learning

Abstract: Our research investigates the application of single-class Support Vector Machine (SVM) for anomaly detection, which is critical for predictive maintenance. The study utilizes real-world ...
IEEE

Enhancing Mobile App Recommendations With Crowdsourced Educational Data Using Machine Learning and Deep Learning

Abstract: In the rapidly evolving digital landscape, personalized recommendations have become essential for enhancing user experience. Machine learning models analyze user behavior patterns to suggest ...
IEEE

Machine Learning-based Customer Segmentation with Optimal Cluster Selection

In Algorithms for Machine Learning Before applying modern clustering algorithms, data was analyzed using rulebased grouping, eye scanning, manual computation of distances, and hierarchical sorting, ...
IEEE

Enhancing Cloud Security: A Multi-Factor Authentication and Adaptive Cryptography Approach Using Machine Learning Techniques

Abstract: The rapid expansion of cloud computing underscores the critical need for advanced security measures to protect sensitive data on remote servers. Authentication is crucial for safeguarding ...