GitHub

weikaih04/Synthetic-Detection-Segmentation-Grounding-Data

A scalable pipeline for composing high-quality synthetic object segments into richly annotated images for object detection, instance segmentation, and visual grounding. High-resolution images with ...
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

Customer Churn Prediction Analysis for Retention Using Ensemble Learning

Abstract: In the 21st century, there is a handful of information on the Internet. It is easy for customers to switch to a competing company in any sector. It is important for a company to retain its ...
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 ...
GitHub

HyperSeg: Towards Universal Visual Segmentation with Large Language Model

This paper aims to address universal segmentation for image and video perception with the strong reasoning ability empowered by Visual Large Language Models (VLLMs). Despite significant progress in ...
IEEE

Predicting Online Purchases Using Six Machine Learning Models Based on Customer Demographics

Abstract: This research paper investigates the predictive power of six machine learning models based on customer demographics to classify online purchasing behavior. The data set consisting of 1000 ...
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 ...