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

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

Visual Malware Classification Using a CNN

Abstract: Malware classification m ethods a re o ften costly, requiring constant retraining and large amounts of computing power in order to support large models that analyze software in numerous ways ...
IEEE

Superpixel-Integrated Dual-Stage Mamba for Hyperspectral Image Classification

Abstract: Hyperspectral image (HSI) classification plays a key role in remote sensing applications such as land cover mapping and environmental monitoring. Mamba is a state-space-based model that has ...
CNN

Trump administration quietly canceled the nation’s largest solar project

The Trump administration’s cancellation of the largest solar project in the United States has sparked confusion and concern among Republicans and Democrats alike. Known as the Esmeralda 7, the ...
IEEE

Robust X-ray Image Classification using Vision Transformers: A Comparative Study with Convolutional Neural Networks

Abstract: Accurate classification of X-ray images is crucial for detecting COVID-19 and pneumonia cases. This study compares the performance of Vision Transformers (ViTs) and Convolutional Neural ...
IEEE

Cross-Domain Hyperspectral Image Classification via Mamba–CNN and Knowledge Distillation

Abstract: Domain adaptation (DA)-based cross-domain hyperspectral image (HSI) classification methods have garnered significant attention. The majority of DA techniques utilize models based on ...
IEEE

A Lightweight Spatial–Spectral Deformable CNN for UAV Hyperspectral Image Classification

Abstract: In recent years, uncrewed aerial vehicle (UAV) technology has shown great potential for application in hyperspectral image (HSI) classification tasks due to its advantages of flexible ...
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

Applying Pseudo-Labels to Partially Labeled Datasets Using the Latent Space Representation of Autoencoders for Image Classification

Abstract: In this paper the feature extraction capabilities of aut encoders were leveraged to perform classification of data when only a very limited number of training datapoints are labeled. The ...
IEEE

ECG Heartbeat Classification Using CNN Autoencoder Feature Extraction and Attention-Augmented BiLSTM Classifier

Abstract: The electrocardiogram (ECG) is a primary non-invasive technique for recording the heart’s electrical activity, but the complexity and subjectivity of manual interpretation have driven the ...