IEEE

Classification of Kidney Abnormalities in CT Images using Deep Learning

Abstract: The CT Kidney Dataset is a structured and medically significant collection of Computed Tomography (CT) scan images, curated for the i m p ro v em en t and growth of AI-predicted diagnostic ...
IEEE

Texture Features-Based Machine Learning for Classification of Cervical Cell Microscopic Images

Abstract: Machine learning has been developed in biomedical science as a clinical decision-support technique. It can automatically recognize patterns in a given dataset to perform predictions and data ...
IEEE

Operator Chain Detection in Image Forensics Using a Two-Stream CNN

Abstract: The advent of image-manipulation techniques and manipulation operator chains has raised the problem of identifying edited photos to prominence in information forensics. Existing forensic ...
IEEE

Temporal-Spatial Feature Extraction in IoT-Based SCADA System Security: Hybrid CNN-LSTM and Attention-Based Architectures for Malware Classification and Attack Detection

Abstract: This research presents a Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) model developed for malware classification from IoT devices in the SCADA system and for ...
IEEE

An Interpretable Brain Tumour Classification Approach using Machine Learning and CNN-based features

Abstract: Cancer, a disease that does not discriminate; impacting people from all walks of life. Numerous types of cancer affect humans, each with distinct characteristics and treatment approaches.
IEEE

BreNet: Attention-Enhanced Multi-Scale CNN Framework for Breast Cancer Classification in Histopathological Images

Abstract: Breast cancer remains a leading cause of mortality among women worldwide, emphasizing the critical importance of early and accurate detection in improving patient outcomes and treatment ...
News-Medical.Net

CNN-based system improves lung nodule detection and classification

Lung cancer remains the leading cause of cancer-related mortality worldwide. Early detection of pulmonary nodules is crucial for timely diagnosis and effective treatment.
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

Brain Cancer MRI Classification using CNN Architectures with Grid Search Enhanced with Coordinate Ascent Optimization

Abstract: Magnetic resonance imaging (MRI) is an important tool for brain cancer diagnosis and classification. Combined with modern convolutional neural network (CNN) technology, it can effectively ...
IEEE

Nnmamba: 3D Biomedical Image Segmentation, Classification and Landmark Detection with State Space Model

Abstract: In biomedical image analysis, developing architectures that effectively capture long-range dependencies is crucial. Traditional Convolutional Neural Networks (CNNs) are constrained by their ...
IEEE

3D CT Liver Images Lesion Extraction and Classification for Using 3D-CNN with GLRLM

Abstract: The imaging technique known as computed tomography (CT) is often considered to be the most reliable way for non-invasive diagnosis. Through the use of three-dimensional (3D) computed ...
IEEE

Efficient and Interpretable Otoscopic Image Classification via Distilled CNN With Adaptive Channel Attention

Abstract: Accurate classification of otoscopic ear images is crucial for early diagnosis of ear pathologies such as Chronic Otitis Media, Earwax Plug, and Myringosclerosis. In this study, we propose a ...