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

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

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

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 ...
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 ...
CNN

I’ve had the viral Shark CryoGlow LED Mask for over a year. Here’s why it’s the only one I’ll ever use

LED masks seem to be the “it” skin care device of the moment. In general, they’ve been shown to stimulate skin’s collagen and elastin production using specific wavelengths of light, which correlate to ...
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 ...