IEEE1mon
Exploring Progress in Multivariate Time Series Forecasting: Comprehensive Benchmarking and Heterogeneity Analysis
Abstract: Multivariate Time Series (MTS) analysis is crucial to understanding and managing complex systems, such as traffic and energy systems, and a variety of approaches to MTS forecasting have been ...
IEEE6d
Geographically Weighted Convolutional Long Short-Term Memory Neural Networks: A Geospatial Deep Learning Model for Monthly NDVI Prediction
Abstract: Vegetation is a key component of biodiversity and ecosystem stability. The normalized difference vegetation index (NDVI) is widely used to monitor the vegetation growth status. Timely ...
IEEE16d
Dedicated 3D Printed Radioactive Phantoms With
Abstract: This study explores the potential of digital light processing to 3D print radioactive phantoms for high-resolution positron emission tomography (PET). Using a slightly modified desktop 3D ...
IEEE25d
BED-YOLO: An Enhanced YOLOv8 for High-Precision Real-Time Bearing Defect Detection
Abstract: In industrial production, precise detection of bearing defects is crucial for optimal machinery performance and maintenance, directly impacting the efficiency of industrial systems and the ...
IEEE24d
RMT-YOLOv9s: An Infrared Small Target Detection Method Based on UAV Remote Sensing Images
Abstract: Unmanned aerial vehicles (UAVs) and infrared imaging technology have numerous applications in civilian fields. To address the issues of low accuracy resulting from complex ground backgrounds ...
IEEE27d
Asynchronous Functional Brain Network Construction with Spatiotemporal Transformer for MCI Classification
Abstract: Construction and analysis of functional brain networks (FBNs) with resting-state functional magnetic resonance imaging (rs-fMRI) is a promising method to diagnose functional brain diseases.
IEEE29d
Data- and Physics-driven Deep Learning Based Reconstruction for Fast MRI: Fundamentals and Methodologies
Abstract: Magnetic Resonance Imaging (MRI) is a pivotal clinical diagnostic tool, yet its extended scanning times often compromise patient comfort and image quality, especially in volumetric, temporal ...
IEEE24d
Beyond Dehazing: Learning Intrinsic Hazy Robustness for Aerial Object Detection
Abstract: Accurate object detection in aerial imagery is crucial across numerous applications. However, haze can significantly degrade the performance of normal detectors, presenting a substantial ...
IEEE27d
Ensemble-Enhanced Semi-Supervised Learning with Optimized Graph Construction for High-Dimensional Data
Abstract: Graph-based methods have demonstrated exceptional performance in semi-supervised classification. However, existing graph-based methods typically construct either a predefined graph in the ...
IEEE23d
Scalable Model, Parameter Extraction of GaN Schottky Barrier Diode (SBD) and Its Application in C-Band Limiter Design
Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=16 ...
IEEE24d
Sliding Optimal Tracking Control of Autonomous Underwater Vehicles with Adaptive Dynamic Programming
Abstract: To improve the tracking performance of Autonomous Underwater Vehicles (AUV), a sliding optimal tracking control method for linear continuous systems is proposed with Adaptive Dynamic ...
IEEE1mon
Ghost Imaging in the Dark: A Multi-Illumination Estimation Network for Low-Light Image Enhancement
Abstract: It is well known that the diverse causes of low-light images challenge the adaptability of enhancement algorithms in uncertain environments. Most deep learning-based algorithms only learn ...