Search Results for author:
Found 26 papers, 4 papers with code
Unsupervised Band Selection Using Fused HSI and LiDAR Attention Integrating With Autoencoder
These approaches overlook the potential benefits of integrating multiple data sources, such as Light Detection and Ranging (LiDAR), and is further challenged by the limited availability of labeled data in HSI processing, which represents a significant obstacle.
LiDAR-Guided Cross-Attention Fusion for Hyperspectral Band Selection and Image Classification
The fusion of hyperspectral and LiDAR data has been an active research topic.
HSIMamba: Hyperpsectral Imaging Efficient Feature Learning with Bidirectional State Space for Classification
HSIMamba is designed to process data bidirectionally, significantly enhancing the extraction of spectral features and integrating them with spatial information for comprehensive analysis.
Surface Reconstruction from Point Clouds via Grid-based Intersection Prediction
On the other hand, UDF-based methods can effectively represent open surfaces but often introduce noise, leading to artefacts in the mesh.
Polyhedral Surface: Self-supervised Point Cloud Reconstruction Based on Polyhedral Surface
This method provides more flexible to represent sharp feature and surface boundary on open surface.
Semi-Federated Learning: Convergence Analysis and Optimization of A Hybrid Learning Framework
To tackle this issue, we propose a semi-federated learning (SemiFL) paradigm to leverage the computing capabilities of both the BS and devices for a hybrid implementation of centralized learning (CL) and FL.
Performance Analysis and Optimization of Reconfigurable Multi-Functional Surface Assisted Wireless Communications
To realize a self-sustainable communication system, we investigate the use of MF-RIS in improving the sum-rate of multi-user wireless networks.
Multi-Functional Reconfigurable Intelligent Surface: System Modeling and Performance Optimization
In this paper, we propose and study a multi-functional reconfigurable intelligent surface (MF-RIS) architecture.
SuperUDF: Self-supervised UDF Estimation for Surface Reconstruction
The key insight is that if the UDF is estimated correctly, the 3D points should be locally projected onto the underlying surface following the gradient of the UDF.
Tensorformer: Normalized Matrix Attention Transformer for High-quality Point Cloud Reconstruction
Surface reconstruction from raw point clouds has been studied for decades in the computer graphics community, which is highly demanded by modeling and rendering applications nowadays.
Meta-DM: Applications of Diffusion Models on Few-Shot Learning
In the field of few-shot learning (FSL), extensive research has focused on improving network structures and training strategies.
Few-Shot Learning
Unsupervised Few-Shot Image Classification
Semi-Federated Learning for Collaborative Intelligence in Massive IoT Networks
Implementing existing federated learning in massive Internet of Things (IoT) networks faces critical challenges such as imbalanced and statistically heterogeneous data and device diversity.
Balancing Accuracy and Integrity for Reconfigurable Intelligent Surface-aided Over-the-Air Federated Learning
Under perfect channel state information (CSI), the new framework minimizes the aggregated model's distortion and retains the local models' recoverability by optimizing the transmit beamformers of the devices, the receive beamformers of the BS, and the RIS configuration in an alternating manner.
Mirror Complementary Transformer Network for RGB-thermal Salient Object Detection
Thus, the key problem of RGB-T SOD is to make the features from the two modalities complement and adjust each other flexibly, since it is inevitable that any modalities of RGB-T image pairs failure due to challenging scenes such as extreme light conditions and thermal crossover.
Resilience in Industrial Internet of Things Systems: A Communication Perspective
Industrial Internet of Things is an ultra-large-scale system that is much more sophisticated and fragile than conventional industrial platforms.
Safeguarding NOMA Networks via Reconfigurable Dual-Functional Surface under Imperfect CSI
This paper investigates the use of the reconfigurable dual-functional surface to guarantee the full-space secure transmission in non-orthogonal multiple access (NOMA) networks.
Towards Communication-Learning Trade-off for Federated Learning at the Network Edge
In this letter, we study a wireless federated learning (FL) system where network pruning is applied to local users with limited resources.
Research on Resource Allocation for Efficient Federated Learning
In this framework, we minimize the weighted sum of system cost and learning cost by optimizing bandwidth, computing frequency, power allocation and subcarrier assignment.
Small-scale Bright Blobs Ejected from a Sunspot Light Bridge
From the transition region images we find an average projected area of $0. 57\pm0. 37$ Mm$^{2}$ for the blobs.
Solar and Stellar Astrophysics
Intelligent Reflecting Surface Aided Multi-Cell NOMA Networks
This paper proposes a novel framework of resource allocation in intelligent reflecting surface (IRS) aided multi-cell non-orthogonal multiple access (NOMA) networks, where a sum-rate maximization problem is formulated.
Coronal heating by MHD waves
In this review we focus on recent advances in our understanding of MHD wave heating mechanisms.
Solar and Stellar Astrophysics
Federated Learning in Multi-RIS Aided Systems
This paper investigates the problem of model aggregation in federated learning systems aided by multiple reconfigurable intelligent surfaces (RISs).
Information Theory Signal Processing Information Theory
Resource Allocation for Multi-Cell IRS-Aided NOMA Networks
This paper proposes a novel framework of resource allocation in multi-cell intelligent reflecting surface (IRS) aided non-orthogonal multiple access (NOMA) networks, where an IRS is deployed to enhance the wireless service.
Gastroscopic Panoramic View: Application to Automatic Polyps Detection under Gastroscopy
The main contributions of this paper are: firstly, a gastroscopic panorama reconstruction method is developed.
Improved Face Detection and Alignment using Cascade Deep Convolutional Network
Real-world face detection and alignment demand an advanced discriminative model to address challenges by pose, lighting and expression.
adaptive direction information in differential evolution for numerical optimization
In most of the DE algorithms, the neighborhood and direction information are not fully and simultaneously exploited to guide the search.
