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

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

A Comparative Study of CNN and Transformer Models for Image Recognition in Autonomous Driving

Abstract: An autonomous driving system requires efficient image recognition to interpret the environment, detect obstacles, and make real-time decisions. This study compares Convolutional Neural ...
IEEE

Sample Augmentation and Balance Approach for Improving Classification Performance With High-Resolution Remote Sensed Image

Abstract: High-resolution remote sensing images can provide detailed information for land cover classification. However, the performance of a classifier depends on the quality and quantity of training ...
IEEE

NSCLC histological subtype classification from CT scans using generalist 3D medical foundation models

Abstract: Lung cancer is one of the leading causes of cancer-related deaths worldwide, with Non-Small Cell Lung Cancer (NSCLC) accounting for approximately 85% of all cases. Accurate histological ...
IEEE

Automated Leaf Disease Detection using a Hybrid CNN-BiLSTM Model for Smart Agriculture

Abstract: The mitigation of crop losses and the sustainability of agriculture rely on the prompt identification of foliar diseases. In large-scale agriculture, conventional identification methods such ...
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Shapiro approves SEPTA's plan to use capital project money to fund operations for 2 years

Pennsylvania Gov. Josh Shapiro on Monday approved SEPTA's plan to use capital project money to fund daily operations for the next two years, meaning the transit authority's "doomsday" service cuts ...
IEEE

Vision Mamba Distillation for Low-Resolution Fine-Grained Image Classification

Abstract: Low-resolution fine-grained image classification has recently made significant progress, largely thanks to the super-resolution techniques and knowledge distillation methods. However, these ...