Using Machine Learning Data to Achieve Sustainability, Performance and Governance Goals

In an environment defined by labor shortages, rising uptime expectations and pressure to improve overall equipment effectiveness (OEE), simple data collection is no longer enough.
IEEE

Comparative Analysis of Traditional and Deep Learning Based Customer Segmentation Models in Online Retail

Abstract: Customer segmentation is the process by which customers are divided into different groups based on shared features, behaviors, or needs. This assists companies in optimizing resource ...
IEEE

Deep Learning-Enhanced Ultrasound Analysis: Classifying Breast Tumors Using Segmentation and Feature Extraction

Abstract: Breast cancer remains a significant global health challenge, requiring accurate and effective diagnostic methods for timely treatment. Ultrasound imaging is a valuable diagnostic tool for ...
IEEE

Brain Tumor Segmentation Using Multi-Task Learning

Abstract: For cancer diagnosis and treatment planning, accurate and reliable brain tumor segmentation is crucial. In this paper, a CNN encoder-decoder-based multi-task learning method is proposed.
IEEE

Focal Adhesions Segmentation Using Deep Learning

Abstract: Focal Adhesions (FAs) are crucial for various cellular processes, including proliferation, survival, and migration. Traditional segmentation methods, such as the Focal Adhesion ...
IEEE

Enhancing Customer Care and Resource Management through Machine Learning: Accurate Forecasting of Consumer Behavior and Optimal Resource Allocation

Abstract: This research paper examines the application of machine learning in predictive customer service, with the aim of improving customer satisfaction and retention. The study investigates the ...
IEEE

Class and Data-Incremental Learning Framework for Baggage Threat Segmentation via Knowledge Distillation

Abstract: With air travel growing rapidly worldwide, airports are busier than ever, making efficient security screening a top priority. To meet this growing demand, various advanced X-ray baggage ...
IEEE

Predictive Modelling of Customer Lifetime Value Using AI and Machine Learning Algorithms

Abstract: Traditional techniques for predicting Customer Lifetime Value (CLV), such as RFM and linear regression, typically fall short when it comes to managing large datasets, identifying non-linear ...
IEEE

Customer Churn Prediction in the Telecommunication Industry Using Multiple Machine Learning Algorithms

Abstract: In the telecommunications sector, financial losses can be substantial due to customer churn. This study explores the prediction of churn in the industry using four popular machine learning ...
IEEE

Intrusion Detection System Using Machine Learning Based on NSL KDD Dataset

Abstract: Todays digital era network may become unstable due to malicious activity on the Internet. One of the best protection methods is an intrusion detection system (IDS), which lowers security ...
IEEE

Fake News Detection Using Machine Learning Techniques

Abstract: These days, wide spread of fake news on different social media platforms and different news sources are one of the strong reasons to cause social damage which is a serious concern. Through ...
IEEE

Predictive Analytics in Mental Health: Machine Learning Models for Major Depressive Disorder Detection using Sensor Data

Abstract: The recent integration of Machine Learning (ML) and sensor technologies in healthcare, particularly for diagnosing Major Depressive Disorder (MDD), has paved the way for advanced predictive ...