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

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

Automatic Persian Speech Emotion Recognition: A CNN-Based Approach Using PDREC and ShEMO Datasets

Abstract: The need for advanced Speech Emotion Recognition (SER) systems has grown with the development of human-machine interaction technologies. This paper introduces a CNN model specifically ...
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 ...
IEEE

Heart Disease Classification using FusionNet to Extract SpatioTemporal Features from ECG Signal

Abstract: An electrocardiogram (ECG) is a foundational tool for diagnosing cardiovascular diseases. However, the assessment of ECG data often depends on the subjective expertise of medical ...
Yahoo

Democrat James Walkinshaw will win US House seat in Virginia special election, narrowing GOP majority, CNN projects

Republican Stewart Whitson, left, and Democrat James Walkinshaw are campaigning to represent Virginia’s 11th congressional district. - AP Democrat James Walkinshaw will win a special election in ...
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 ...
CNN

Democrat James Walkinshaw will win US House seat in Virginia special election, narrowing GOP majority, CNN projects

Democrat James Walkinshaw will win a special election in Virginia’s 11th Congressional District, CNN’s Decision Desk projects, bolstering Democratic numbers in the House and cutting down on an already ...