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

Explainable Brain Tumor Classification using CNN and GradCAM

Abstract: One of the most critical neurological conditions is Brain tumors, timely and correct diagnosis is needed for effective treatment. Advances in neuroimaging technology such as MRI, limitations ...
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

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 ...
IEEE

Auto-ROI for Indonesian Primary Thoracic Dataset in CNN-Pneumonia Classification

Abstract: Pneumonia is one of the most serious lung infections and remains a leading cause of death in children under five years of age, especially in developing countries such as Indonesia. Diagnosis ...
AOL

Democrat Taylor Rehmet flips a Texas state Senate seat Trump won by 17 points, CNN projects

Democrats notched another victory Saturday in special elections during President Donald Trump’s second term, flipping a seat in the Texas Senate that Trump won by 17 points in 2024. Taylor Rehmet, a ...
IEEE

Enhancing CNN-Based Motion Sickness Detection using EEG Signals Weighted by Motion Sickness Dose Value

Abstract: With the advancement of autonomous driving technologies, passengers increasingly engage in non-driving activities. However, these activities are often limited by motion sickness (MS), which ...
IEEE

Dual-Graph Knowledge Distillation Meets Multiscale CNN: A Novel Ensemble Approach for Few-Shot Hyperspectral Image Classification

Hyperspectral image (HSI) classification aims at categorizing each pixel in an HSI, facilitating precise identification and differentiation of various land cover types. In recent years, graph neural ...
IEEE

Multilevel Multimodal CNN–Transformer Fusion Network for Land Use and Land Cover Classification

Abstract: In remote sensing (RS), convolutional neural networks (CNNs) are well-recognized for their spatial–spectral feature extraction capabilities, whereas vision transformers (ViTs), which ...
IEEE

Hybrid CNN-Swin Framework for Detection and Classification of Potato Leaf Diseases

Abstract: Timely and accurate identification of plant diseases is essential for sustainable agricultural practices and food security. This study presents a deep learning-based diagnostic framework ...
IEEE

RMNet: Dual-Dimensional Difference Recalibration-Guided CNN-VMamba Synergistic Network for Remote Sensing Image Change Captioning

Abstract: Global surface changes are increasingly monitored using multi-temporal remote sensing technologies. As an emerging technology, change captioning can organically integrate the location ...
TheWrap

Joe Rogan Mocks AI-Altered Alex Pretti Image Accidentally Aired by MS NOW: ‘The Opposite of What CNN Did to Me’ | Video

Joe Rogan got his eyebrows all the way up on Wednesday when discussing an image of Minneapolis ICE shooting victim Alex Pretti that was mistakenly featured on an MS NOW segment which had clearly been ...