IEEE

Enhanced CNN Architecture with Residual Blocks and Regularization for AI-Generated Image Detection

Abstract: The growing popularity of social networks has led to an unprecedented surge in the number of digital images shared daily. As a result, ensuring the authenticity of these images has become a ...
IEEE

Fine-Grained Feature Extraction in Key Sentence Selection for Explainable Sentiment Classification Using BERT and CNN

Abstract: Online product reviews provide valuable insights into customer sentiment toward products; however, they often contain multiple sentences with redundant and non-essential content, making it ...
IEEE

A Semantic Transferable Feature Extraction Strategy for Cross-Domain Detection

Abstract: Surface defect detection is important for ensuring industrial manufacturing quality. Convolutional neural networks significantly improve the detection performance. However, surface defects ...
IEEE

MonoICT: A Monocular 3-D Object Detection Model Integrating CNN and Transformer

Abstract: In the field of autonomous driving, 3-D object detection is a crucial technology. Visual sensors are essential in this area and are widely used for 3-D object detection tasks. Recent ...
IEEE

A Hybrid Machine Learning Approach Utilizing CNN Feature Extraction with Traditional Classifier to Identify Strawberry Leaf Diseases

Abstract: Strawberry production is globally significant because it contains high nutrients. Strawberry leaf disease shapes a significant barrier to strawberry cultivation worldwide. Numerous ...
IEEE

YOLOv10n-Based Defect Detection in Power Insulators: Attention Enhancement and Feature Fusion Optimization

Abstract: In modern power systems, insulators, as key components of transmission lines, are crucial for defect detection for the safe operation of power grids. Aiming at the problems of low efficiency ...
IEEE

RoBERTa-Based Multi-Feature Integrated BiLSTM and CNN Model for Ceramic Review Analysis

Abstract: To address the limitation that the Robustly Optimized BERT Pretraining Approach (RoBERTa) may not effectively capture local dependencies and salient features within the text, we propose a ...