IEEE

Explainable AI in Medical Imaging: A Hybrid CNN and Random Forest Framework for Brain Tumor Detection

Abstract: A critical disease, a brain tumor must be categorized correctly if treatment and patient management are to be directed. Due to interpretational bias by individuals and errors that are rife ...
IEEE

Multi-scale Feature Learning with CNN-RNN-Attention Framework for ECG-based Cancer Therapy-Related Cardiac Dysfunction Detection

Cancer therapy-related cardiac dysfunction (CTRCD) is an increasingly significant concern due to cardiac function deterioration caused by anticancer drug side effects. While echocardiography is the ...
Ukrainska Pravda on MSN

Trump official refuses to rule out military takeover of Greenland

White House Deputy Chief of Staff Stephen Miller has stated that Washington insists Greenland should become part of the US as ...
KVIA

How right-wing media inspired Trump’s ‘Donroe Doctrine’

While describing the US military operation in Venezuela on Saturday, President Trump referenced a two-word title for his ...
IEEE

Ensemble CNN Architecture with Multi-Modal Disease Detection for Sustainable Banana Crop Management: An Integrated Mobile Framework

The inefficiency of manual detection methods makes diagnosing banana crop diseases a serious threat to the agricultural sector. In this paper, we introduce ensemble deep learning of ResNet50, ...
IEEE

Deepfake Image Recognition using Unified Hybrid Framework of CNN, Transformer, and Frequency Features

Abstract: Deepfake is a technique for manipulating or creating visual and audio content to appear realistic. A person’s face can be replaced, their voice imitated, or a scene made to appear as if it ...
IEEE

Optimizing CNN-Based Video Summarization With Digital Twin Framework for Adaptive Probability Thresholding

Abstract: The rapid growth of video data necessitates efficient summarization techniques to extract critical insights while minimizing computational overhead. This study investigates three pre-trained ...
IEEE

Hybrid CNN-XGBoost Framework for Interpretable ECG Arrhythmia Classification with SHAP-based Analysis

Abstract: Accurate and interpretable detection of cardiac arrhythmias from electrocardiogram (ECG) signals is pivotal for effective cardiovascular disease management. We propose a novel hybrid ...
IEEE

Decoding Depression Progression via Multi-Site Local Field Potentials: A CNN Framework Integrating Spectral and Connectivity Features

Abstract: Major depressive disorder (MDD) is a leading cause of global disability. Previous studies have primarily focused on spectral features or regional brain activity before and after depressive ...
IEEE

Fine Tuning Hyperparameters of Deep Learning Models Using Metaheuristic Accelerated Particle Swarm Optimization Algorithm

Abstract: In recent years, Convolutional Neural Networks (CNNs) have emerged as powerful tools for solving complex real-world problems, particularly in the domain of image processing. The success of ...
IEEE

CNN-Based Deep Learning Framework for Multi-Class Rice Leaf Disease Detection and Classification

Abstract: Being a major contributor to rice production worldwide, rice leaf diseases need to be detected early and correctly to achieve maximum output and reduce losses. Processes based on deep ...
IEEE

Walking Patterns and Gender: A CNN+LSVM Framework for Gait-Based Classification

Abstract: This research provides a unique strategy that combines Convolutional Neural Networks (CNN) and Linear Support Vector Machines (LSVM) to classify gender based on human gait. The suggested ...