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 ...
Journal of Medical Internet Research

Passive Sensing for Mental Health Monitoring Using Machine Learning With Wearables and Smartphones: Scoping Review

Passive sensing via wearable devices and smartphones, combined with machine learning (ML), enables objective, continuous, and noninvasive mental health monitoring. Objective: This study aimed to ...
IEEE

SiamMask-ICDNet: A Hybrid Algorithm of Siamese Neural Network and Mask R-CNN for Island Building Change Detection

Abstract: Timely detection of construction changes on islands is crucial for environmental conservation, resource management, and sustainable development. Current methodologies typically employ ...
IEEE

A Multi-Resolution Hybrid CNN-Transformer Network With Scale-Guided Attention for Medical Image Segmentation

Abstract: Medical image segmentation remains a challenging task due to the intricate nature of anatomical structures and the wide range of target sizes. In this paper, we propose a novel U-shaped ...
IEEE

Multi Detection and Segmentation Coconut Shell for Charcoal Briquette Using Mask R-CNN

Abstract: Coconut shell are the raw material for making high-quality charcoal briquettes, and their quality dramatically affects the quality of the final product. Therefore, assessing and determining ...
IEEE

Novel Mask R-CNN Based Mushroom Cluster Tracking in Time-Lapse Images From a Farm Environment

Abstract: This study aims to develop a novel deep learningbased approach to support the automated mushroom growth monitoring using an object tracking algorithm in conjunction with instance ...
IEEE

A Verilog based Approach for Object Detection using CNN

Abstract: A Convolutional Neural Network (CNN) are a class of artificial neural networks specifically designed to process data with a grid-like topology, such as images, making them well-suited for ...
IEEE

Mask R-CNN-based bushing segmentation with refined feature extraction and precise localization

Abstract: Accurate localization and segmentation of power equipment are critical for automated inspection systems, particularly in detecting structural and thermal anomalies. However, the task remains ...
IEEE

Data-Driven Solutions for Human Trafficking: Detection and Impact Analysis Using Machine Learning

Abstract: Human trafficking is a serious problem that requires new ideas and data-driven approaches to identify and solve. In this study, we analyze large datasets to identify patterns and anomalies ...
IEEE

Automated Optic Disc and Cup Segmentation Using Mask R-CNN for Glaucoma Assessment

Abstract: Glaucoma, a leading cause of irreversible blindness, requires precise segmentation of the optic disc and optic cup in fundus images for early diagnosis and progression monitoring. This study ...
IEEE

Synthetic Data Augmentation for Enhanced Chicken Carcass Instance Segmentation

Abstract: The poultry industry has been driven primarily by broiler chicken production and has grown into the world’s largest animal protein sector. Automated detection of chicken carcasses on ...