IEEE

Retinal Fundus Image Classification Using Generative Adversarial Networks

Abstract: This study presents an innovative method for classifying retinal fundus images using a novel combination of Generative Adversarial Networks (GANs) and Inception V3. This unique method has ...
IEEE

A Hybrid CNN-SEU-Net Approach for Improved Melanoma Detection in Dermoscopy Images : Combining CNN and SEU-Net for Robust Melanoma Detection

Abstract: Melanoma is a highly aggressive form of skin cancer with high mortality rates if not diagnosed early. Accurate diagnosis poses significant challenges, particularly for nonspecialist ...
IEEE

A CNN-Transformer Approach for Image-Text Multimodal Classification with Cross-Modal Feature Fusion

Abstract: This study proposes an image-text multimodal classification algorithm based on a combination of convolutional neural networks (CNN) and Transformer, aiming to solve the key problems in ...
IEEE

Enhancing Fault Detection and Classification in Wind Farm Power Generation Using Convolutional Neural Networks (CNN) by Leveraging LVRT Embedded in Numerical Relays

Abstract: Real-time fault detection and classification are important for power system stability and resilience of the power grid to minimize downtime and prevent cascading failures. Numerical relays ...
IEEE

HC-Mamba: Remote Sensing Image Classification via Hybrid Cross-Activation State–Space Model

Abstract: Remote sensing image classification plays a crucial role in scene understanding task interpretation. Currently, remote sensing image classification is constrained by the complexity, ...
IEEE

Image Classification Model for Data Sentry of Plant Diseases Using Convolutional Neural Networks

Abstract: This study examines the effectiveness of using machine learning-based image recognition model for classifying common diseases in crops. This study addresses the critical need for swift and ...
IEEE

LSTA-CNN: A Lightweight Spatiotemporal Attention-Based Convolutional Neural Network for ASD Diagnosis Using EEG

Abstract: Electroencephalography (EEG) is an effective assessment tool to identify autism spectrum disorders with low cost, and deep learning has been applied in EEG analysis for extracting meaningful ...
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

Multi-Scale Feature Extraction for ECG Beat Classification Using a CNN-Transformer Network with Imbalance Mitigation

Abstract: Deep learning models have become popular for classifying electrocardiogram (ECG) heartbeats, yet traditional Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) have ...
IEEE

Adaptive SimSiam Self-Supervised Networks with Hybrid PIO for Hyperspectral Image Classification

Abstract: Hyperspectral imaging (HSI) provides rich spectral information across hundreds of bands, offering significant potential for fine-grained classification in remote sensing. However, the high ...
Bisnow

Addison Plans Huge Mixed-Use Project At DART Silver Line Stop

Addison plans to turn its new stop on Dallas Area Rapid Transit’s commuter rail to the airport into a massive mixed-use district. Addison City Council awarded Quadrant Investment Properties a master ...
IEEE

CNN-Enhanced Hypergraph Attention Network for Hyperspectral Image Classification

Abstract: Recently, graph neural networks (GNNs) have attracted great attention and achieved outstanding success in hyperspectral image (HSI) classification. However, most existing methods rely on ...