Search Results for author:
Found 27 papers, 3 papers with code
Gaussian Garments: Reconstructing Simulation-Ready Clothing with Photorealistic Appearance from Multi-View Video
We introduce Gaussian Garments, a novel approach for reconstructing realistic simulation-ready garment assets from multi-view videos.
Equity-aware Load Shedding Optimization
Load shedding is usually the last resort to balance generation and demand to maintain stable operation of the electric grid after major disturbances.
Sparse Attention-driven Quality Prediction for Production Process Optimization in Digital Twins
By iteratively mapping the real-world data reflecting equipment operation status and product quality indicators in the digital twin, we adopt a quality prediction model for production process based on self-attention-enabled temporal convolutional neural networks.
Edge Computing for IoT: Novel Insights from a Comparative Analysis of Access Control Models
IoT edge computing positions computing resources closer to the data sources to reduce the latency, relieve the bandwidth pressure on the cloud, and enhance data security.
CourseGPT-zh: an Educational Large Language Model Based on Knowledge Distillation Incorporating Prompt Optimization
Moreover, considering the alignment of LLM responses with user needs, a novel method for discrete prompt optimization based on LLM-as-Judge is introduced.
Adaptive Online Model Update Algorithm for Predictive Control in Networked Systems
In this article, we introduce an adaptive online model update algorithm designed for predictive control applications in networked systems, particularly focusing on power distribution systems.
4D-DRESS: A 4D Dataset of Real-world Human Clothing with Semantic Annotations
Addressing this gap, we introduce 4D-DRESS, the first real-world 4D dataset advancing human clothing research with its high-quality 4D textured scans and garment meshes.
Computation Rate Maximization for Wireless Powered Edge Computing With Multi-User Cooperation
Simulation results show that the performance of the proposed algorithms is comparable to that of the exhaustive search method, and the deep learning-based algorithm significantly reduces the execution time of the algorithm.
TranDRL: A Transformer-Driven Deep Reinforcement Learning Enabled Prescriptive Maintenance Framework
Industrial systems demand reliable predictive maintenance strategies to enhance operational efficiency and reduce downtime.
Optimal Driving Model for Connected and Automated Electric Freight Vehicles in a Wireless Charging Scenario at Signalised Intersections
In this study, wireless charging technology is employed to construct a complex driving scenario including urban roads and dynamic wireless charging facilities.
Communication Efficient Distributed Learning over Wireless Channels
Vertical distributed learning exploits the local features collected by multiple learning workers to form a better global model.
Multi-faceted Graph Attention Network for Radar Target Recognition in Heterogeneous Radar Network
In this paper, a two-stream semantic feature fusion model, termed Multi-faceted Graph Attention Network (MF-GAT), is proposed to greatly improve the accuracy in the low SNR region of the heterogeneous radar network.
Spatio-Temporal-Frequency Graph Attention Convolutional Network for Aircraft Recognition Based on Heterogeneous Radar Network
This paper proposes a knowledge-and-data-driven graph neural network-based collaboration learning model for reliable aircraft recognition in a heterogeneous radar network.
Improved Sensing and Positioning via 5G and mmWave radar for Airport Surveillance
This paper explores an integrated approach for improved sensing and positioning with applications in air traffic management (ATM) and in the Advanced Surface Movement Guidance and Control System (A-SMGCS).
Deep learning-based UAV detection in the low altitude clutter background
A low-altitude UAV detection method based on deep contrastive learning is proposed to address the above problems: Concretely, a low-altitude UAV radar echo model under low-altitude clutter interference is first established.
Medium Access Control protocol for Collaborative Spectrum Learning in Wireless Networks
Based on the algorithm we provide a medium access control protocol which allows distributed implementation of the algorithm in ad-hoc networks.
RSS-based Multiple Sources Localization with Unknown Log-normal Shadow Fading
Then we utilize the K-means clustering method to obtain the rough locations of the off-grid sources as the initial feasible point of the ML estimator.
Converging Radar and Communications in the Superposition Transmission
Under communications quality-of-service (QoS) constraints, the joint performance region of communications sum rate and radar estimation error variance is studied.
Impact of DER Communication Delay in AGC: Cyber-Physical Dynamic Simulation
Distributed energy resource (DER) frequency regulations are promising technologies for future grid operation.
Low-dimensional Denoising Embedding Transformer for ECG Classification
However, the high-dimensional embedding obtained via 1-D convolution and positional encoding can lead to the loss of the signal's own temporal information and a large amount of training parameters.
Demand-Side Scheduling Based on Multi-Agent Deep Actor-Critic Learning for Smart Grids
Each household is a decentralized agent with partial observability, which allows scalability and privacy-preservation in a realistic setting.
Decentralized Learning for Channel Allocation in IoT Networks over Unlicensed Bandwidth as a Contextual Multi-player Multi-armed Bandit Game
We study a decentralized channel allocation problem in an ad-hoc Internet of Things network underlaying on the spectrum licensed to a primary cellular network.
Learning Confidence Sets using Support Vector Machines
The goal of confidence-set learning in the binary classification setting is to construct two sets, each with a specific probability guarantee to cover a class.
A Survey on Consensus Mechanisms and Mining Strategy Management in Blockchain Networks
This survey is motivated by the lack of a comprehensive literature review on the development of decentralized consensus mechanisms in blockchain networks.
Cryptography and Security
Decentralized Caching for Content Delivery Based on Blockchain: A Game Theoretic Perspective
In this paper, we propose a decentralized framework of proactive caching in a hierarchical wireless network based on blockchains.
Networking and Internet Architecture
On Reject and Refine Options in Multicategory Classification
In many real applications of statistical learning, a decision made from misclassification can be too costly to afford; in this case, a reject option, which defers the decision until further investigation is conducted, is often preferred.
Social Computing for Mobile Big Data in Wireless Networks
Mobile big data contains vast statistical features in various dimensions, including spatial, temporal, and the underlying social domain.
