IEEE

Hybrid CNN-Transformer Model for Accurate Classification of Human Attention Levels Using Workplace EEG Data

Abstract: Accurately detecting human attention levels is a key challenge in cognitive neuroscience, with broad application value in improving productivity. Although Electroencephalography (EEG) ...
IEEE

Deep Learning-Enhanced Ultrasound Analysis: Classifying Breast Tumors Using Segmentation and Feature Extraction

Abstract: Breast cancer remains a significant global health challenge, requiring accurate and effective diagnostic methods for timely treatment. Ultrasound imaging is a valuable diagnostic tool for ...
IEEE

EICSeg: Universal Medical Image Segmentation via Explicit In-Context Learning

Abstract: Deep learning models for medical image segmentation often struggle with task-specific characteristics, limiting their generalization to unseen tasks with new anatomies, labels, or modalities ...
IEEE

An Evaluation of Medical Image Analysis using Image Segmentation and Deep Learning Techniques for Brain-Tumour

Abstract: An aberrant mass of rapidly proliferating brain cells, known as a brain tumour, may develop into various forms of cancer. The segmentation of brain tumours by MRI scans is a challenging but ...
IEEE

Efficient Satellite Image Retrieval Using Shearlet Transforms and Spiking Neurons-Based Liquid Autoencoder Model

Abstract: This paper introduces an innovative content-based image retrieval system for precise and effective retrieval of satellite images. The system integrates liquid autoencoders with shearlet ...
IEEE

Brain MRI Analysis Using CNN-Based Feature Extraction and Machine Learning Techniques to Diagnose Alzheimer's Disease

Abstract: This research focuses on developing a complex framework for automatic diagnosis purposes of Alzheimer's disease from MRI brain data, with emphasis placed on advancement in accuracy towards ...
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

Detection of Single Radio Isotopes Using Mask CNN Approach

Abstract: The detection of radioisotopes via the use of a plastic scintillation detector presents a substantial difficulty. This is mostly owing to the low cross-sections and poor spectrum resolution ...
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

Data-Driven Customer Segmentation in E-Commerce using K-Means Clustering for Personalized Marketing Strategies

Abstract: With the big data era, precision marketing in e-commerce has become ever more important in order to target prospective customers with high relevance. The present research focuses on applying ...
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 ...