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 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 ...
IEEE

Automated Trash Detection and Classification Using CNN: A Deep Learning Approach

Abstract: A research project focuses on creating automated trash detection and classification through convolutional neural networks (CNNs) with an objective to improve waste management systems. The ...
IEEE

TRAM: Transformer-Based Mask R-CNN Framework for Underwater Object Detection in Side-Scan Sonar Data

Abstract: Accurate detection and segmentation of underwater objects in side-scan sonar (SSS) imagery remain challenging due to noise, cluttered backgrounds, and low-contrast conditions. In this paper, ...
IEEE

Fraudulent Credit Card Transaction Monitoring Using Deep Learning: A CNN-LSTM Approach for Single-Transaction Security Identification

Abstract: Credit card cash-out methods have become increasingly complex, with new fraudulent transaction forms emerging continuously. Effective management is hindered by challenges in obtaining ...
IEEE

AI-Powered Defect Detection using Deep Learning: A Pattern-Agnostic Faster R-CNN Approach for SEM Images with GPU Acceleration

Abstract: Semiconductor manufacturing requires highly precise defect detection to ensure product quality and yield. This paper presents a deep learning-based defect detection framework using Faster ...
IEEE

Efficient Machine Learning-Based Semantic Segmentation Algorithm for Consumer-Grade AAV Remote Sensing

Abstract: The computational complexity of the Transformer model grows quadratically with input sequence length. This causes a sharp increase in computational cost and memory consumption for ...
IEEE

Efficient Document Image Classification Using Deep Learning Enhance with CNN Architectures

Abstract: Document image classification has a significant difficulty for the retrieval of digital documents and systems management in recent years. The main goal of this study is to investigate the ...
IEEE

Mental Health Prediction using Machine Learning

Abstract: Major problems in the 21st century are mental health care problems. It can be considered as one of its important evils between men, and its source is in the largeness of awareness among the ...
IEEE

Real Time Traffic Management System using Mask R-CNN and Dynamic Scheduling Algorithm

Abstract: Conventional manual, semi automated and timed traffic control systems are being replaced by more effective technology based systems. A low cost, real time, automated system is necessary for ...
IEEE

Hybrid Attention Driven CNN-Mamba Multimodal Fusion Network for Remote Sensing Image Semantic Segmentation

Abstract: In recent years, the increase of multimodal image data has offered a broader prospect for multimodal semantic segmentation. However, the data heterogeneity between different modalities make ...
IEEE

Machine Learning-based Detection of Web Attacks Using Logistic Model Trees

Abstract: Cyberattacks pose a significant threat to internet security and may cause great damage to businesses. Machine learning methodologies have been widely used to detect cyber intrusions. This ...