IEEE

3D Reconstruction of Steel Rail using Multi-view Cameras and Mask R-CNN

Abstract: This study proposed a method that integrates multi-view image processing, depth estimation, and point cloud generation to accurately reconstruct a 3D model of a rail. The method is tested by ...
IEEE

Physically-Aware Qubit Reuse for Optimized Quantum Circuit Compilation Using Machine Learning

Recently developed quantum computers support mid-circuit measurements, allowing qubit measurement, resetting, and reuse during the execution of quantum circuits. This capability opens new ...
IEEE

Fully Perturbed Self-Ensemble Framework using Cascaded Parallel CNN-Transformer for Semi-Supervised Medical Image Segmentation

Abstract: Semi-supervised learning (SSL) has achieved remarkable progress in the field of medical image segmentation (MIS), but it still faces two main challenges. First, the consistency learning ...
IEEE

Automatic Extraction of Tooth Region for Dental Aesthetic Treatment Using Mask R-CNN

Abstract: In recent years, there has been an increasing interest in the aesthetics of teeth, particularly regarding tooth color. Among the various approaches to improve the appearance of teeth, crown ...
IEEE

Transforming Disability Into Ability: An Explainable Vision-to-Voice Image Captioning Framework Using Transformer Models and Edge Computing

Abstract: Image captioning is an emerging field at the intersection of computer vision and natural language processing (NLP). It has shown great potential to enhance accessibility by automatically ...
IEEE

Lightweight 2D Medical Image Segmentation via a Decoder Using Linear Deformable Convolution and Multi-scale Self-attention

Abstract: Computational resources, which presents a significant challenge in resourceconstrained environments, particularly in developing countries. Consequently, the development of decoding ...
IEEE

Deep Learning for Satellite Image Classification: A Comparative Analysis of CNN and ResNet-18

Abstract: With the ease of classifying land through satellite imaging, remote sensing has captured the Earth observation domain. Traditional methods for analyzing satellite images relied on manual ...
IEEE

Mask augmented Object-Centric Contrastive Learning for Amodal Instance Segmentation

Abstract: Human cognition is robust in estimating depth ordering and occluded regions of objects, including amodal instance segmentation (AIS). Object-centric representation learning (OCRL) is 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 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

Skin Disease Detection Using CNN: 6th International Conference on Innovative Trends in Information Technology(ICITIIT-2025)

Abstract: Skin diseases and it's infectious diseases are the most common health issues, requiring quick and correct diagnosis for appropriate treatment. In this study to describe the uses of ...
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 ...