IEEE5d
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 ...
IEEE15d
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 ...
IEEE13d
Waves and Fields in Inhomogenous Media
Book Abstract: Electrical Engineering/Electromagnetics Waves and Fields in Inhomogeneous Media A Volume in the IEEE Press Series on Electromagnetic Waves Donald G ...
IEEE23d
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 ...
IEEE28d
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 ...
IEEE26d
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
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 ...
IEEE23d
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
FedSN: A Federated Learning Framework over Heterogeneous LEO Satellite Networks
Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=7755 ...
IEEE18d
The Decoupling Concept Bottleneck Model
Abstract: The Concept Bottleneck Model (CBM) is an interpretable neural network that leverages high-level concepts to explain model decisions and conduct human-machine interaction. However, in ...
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 ...