IEEE

Deep Learning-Based Railway Foreign Object Intrusion Intelligent Perception Using Attention-Aggregated Semantic Segmentation

Abstract: Foreign object intrusion detection (FOID) is one of the critical tasks to ensure the safe and efficient operation of trains. Semantic segmentation, which involves pixel-level recognition of ...
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

Semi-Supervised 3-D Medical Image Segmentation Using Multiconsistency Learning With Fuzzy Perception-Guided Target Selection

Abstract: Semi-supervised learning methods based on the mean teacher model have achieved great success in the field of 3-D medical image segmentation. However, most of the existing methods provide ...
IEEE

Telco Customer Churn Prediction Using Composite Deep Learning Technique

Abstract: Customer churn is a critical issue in the telecommunication (Telecom) industry, leading to significant revenue loss and increased customer acquisition costs. To address this, a project was ...
IEEE

Prototypical Metric Segment Anything Model for Data-Free Few-Shot Semantic Segmentation

Abstract: Few-shot semantic segmentation (FSS) is crucial for image interpretation, yet it is constrained by requirements for extensive base data and a narrow focus on foreground-background ...
IEEE

Enhancing Sentiment Analysis of Customer Reviews Using Deep Learning, Data Augmentation and Explainable AI

Abstract: Sentiment analysis of customer reviews is crucial for understanding consumer feedback and improving business strategies in the e-commerce sector. This study proposes an enhanced deep ...
IEEE

Uncertainty Global Contrastive Learning Framework for Semi-Supervised Medical Image Segmentation

Abstract: In semi-supervised medical image segmentation, the issue of fuzzy boundaries for segmented objects arises. With limited labeled data and the interaction of boundaries from different ...
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

Prediction of Customer Satisfaction using Machine Learning Algorithms: Perspectives of Service and Operational Factors in Airline Industry

Abstract: Customer satisfaction in the airline industry is influenced by demographic, service-related, and operational factors. As competition grows and passenger expectations evolve, understanding ...
IEEE

Dynamic Pricing Models in E-Commerce: Exploring Machine Learning Techniques to Balance Profitability and Customer Satisfaction

Abstract: This research investigates the application of Recurrent Neural Networks (RNNs), specifically Long Short-Term Memory (LSTM) networks, paired with gradient-based optimization techniques for ...
IEEE

Dense Segmentation Techniques Using Deep Learning for Urban Scene Parsing: A Review

Abstract: Dense segmentation tasks, including semantic, instance, and panoptic segmentation, are essential for improving our comprehension of urban landscapes. This paper examines various deep ...