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 ...
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

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

Enhancing Liver Cirrhosis Diagnosis Using Machine Learning With Explainable AI and Cross-Validated Hyperparameter Tuning Techniques

Abstract: Cirrhosis is a form of Chronic Liver Disease (CLD) resulting from sustained liver damage from several causes, including viral infection, autoimmune disorders, cholestatic and metabolic ...
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 ...