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

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

Brightness-Enhanced Gastrointestinal Endoscopy Image Classification Using CNN-Based Diagnostic Model

Abstract: This study proposes a framework based on a Cycle-Consistent Generative Adversarial Network (CycleGAN) to improve the image brightness and visual continuity of gastrointestinal (GI) ...
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 ...
Mediaite

CNN Data Guru Warns Trump’s ‘Collapsing’ Approval with Working Class Voters is Dragging Down GOP

CNN’s chief data analyst Harry Enten warned President Donald Trump’s approval rating with a key demographic within his base, non-college voters, was “absolutely collapsing” and dragging the Republican ...
GitHub

Ming-UniVision: Joint Image Understanding and Geneation with a Continuous Unified Tokenizer

🌐 Ming-UniVision is a groundbreaking multimodal large language model (MLLM) that unifies vision understanding, generation, and editing within a single autoregressive next-token prediction (NTP) ...
IEEE

Hybrid Integration of CNN and Kolmogorov–Arnold Networks for Multispectral Image Super-Resolution

Abstract: This letter proposes KAN-based multispectral image super-resolution method (KMSR), a novel deep learning framework for multispectral image (MSI) super-resolution (SR) that integrates ...