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

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

Deep Learning-Based Flood Detection System Using Semantic Segmentation

Abstract: Floods cause immense damage worldwide, resulting in significant financial losses and loss of life. Existing flood detection methods often face limitations, including delays and errors due to ...
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 ...
IEEE

Data-Driven Customer Segmentation in E-Commerce using K-Means Clustering for Personalized Marketing Strategies

Abstract: With the big data era, precision marketing in e-commerce has become ever more important in order to target prospective customers with high relevance. The present research focuses on applying ...
IEEE

Software Estimation Process Improvement using Data Segmentation

Abstract: Estimating software development effort holds pivotal significance in the domains of resource allocation, budgeting, and project planning. Despite this importance, achieving precise ...
IEEE

Deep Learning Based Segmentation of Weed Images in crop fields using U-Net

Abstract: Weeds are problems for crop yields because they exert harmful effects on the yields by competing with cultivated crops for necessary resources like nutrients, sunlight, and soil. As a result ...
IEEE

Extracting Learning Data From Handwritten Notes: A New Approach to Educational Data Analysis Based on Image Segmentation and Generative AI

Abstract: While handwritten notes offer valuable insights into students’ knowledge retention, traditional analysis methods are often time-consuming and limited in scope. This study introduces an ...
IEEE

Optimized Ensemble Learning for Semantic Segmentation of Satellite Imagery Using DeepLabV3+ and UNet With PSO and Cross-Dataset Evaluation

Abstract: Semantic segmentation is critical in remote sensing applications such as urban planning, disaster management, and environmental monitoring. However, segmenting complex satellite images ...
IEEE

Machine Learning and Deep Learning for Loan Prediction in Banking: Exploring Ensemble Methods and Data Balancing

Abstract: The prediction of loan defaults is crucial for banks and financial institutions due to its impact on earnings, and it also plays a significant role in shaping credit scores. This task is a ...
IEEE

Machine Learning for Multi-Class Kidney Tumour Segmentation: Advancing Classification Accuracy

Abstract: Appropriate treatment planning depends heavily on early detection together with accurate sectioning of kidney tumours. The research design introduces a deep learning architecture which ...