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Found 54 papers, 3 papers with code
Destruction and Construction Learning for Fine-Grained Image Recognition
In this paper, we propose a novel "Destruction and Construction Learning" (DCL) method to enhance the difficulty of fine-grained recognition and exercise the classification model to acquire expert knowledge.
OpenArray v1.0: a simple operator library for the decoupling of ocean modeling and parallel computing
In this work, we design a simple computing library to bridge the gap and decouple the work of ocean modeling from parallel computing.
UV Volumes for Real-time Rendering of Editable Free-view Human Performance
Neural volume rendering enables photo-realistic renderings of a human performer in free-view, a critical task in immersive VR/AR applications.
Convolution Forgetting Curve Model for Repeated Learning
The status of forgetting (i. e. the output in the working memory model) is regarded as output function or the convolution result of the memory ability and learning material.
A k-Nearest Neighbor Approach towards Multi-level Sequence Labeling
For the experiments we perform a comparison between using pseudo-data and real world data.
Investigating Multilingual Abusive Language Detection: A Cautionary Tale
Based on our findings, we can conclude that a multilingual optimization of classifiers is not possible even in settings where comparable data sets are used.
RIS Enhanced Massive Non-orthogonal Multiple Access Networks: Deployment and Passive Beamforming Design
A novel framework is proposed for the deployment and passive beamforming design of a reconfigurable intelligent surface (RIS) with the aid of non-orthogonal multiple access (NOMA) technology.
Artificial Intelligence Aided Next-Generation Networks Relying on UAVs
Artificial intelligence (AI) assisted unmanned aerial vehicle (UAV) aided next-generation networking is proposed for dynamic environments.
Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies
Since DARPA Grand Challenges (rural) in 2004/05 and Urban Challenges in 2007, autonomous driving has been the most active field of AI applications.
An Ultra Lightweight CNN for Low Resource Circuit Component Recognition
In this paper, we present an ultra lightweight system that can effectively recognize different circuit components in an image with very limited training data.
Multi-Agent Reinforcement Learning in NOMA-aided UAV Networks for Cellular Offloading
Afterward, a mutual deep Q-network (MDQN) algorithm is proposed to jointly determine the optimal 3D trajectory and power allocation of UAVs.
Path Design and Resource Management for NOMA enhanced Indoor Intelligent Robots
Our simulation results demonstrate that 1) With the aid of NOMA techniques, the communication reliability of IRs is effectively improved; 2) The radio map is qualified to be a virtual training environment, and its statistical channel state information improves training efficiency by about 30%; 3) The proposed DT-DPG algorithm is superior to the conventional deep deterministic policy gradient (DDPG) algorithm in terms of optimization performance, training time, and anti-local optimum ability.
NOMA in UAV-aided cellular offloading: A machine learning approach
A novel framework is proposed for cellular offloading with the aid of multiple unmanned aerial vehicles (UAVs), while non-orthogonal multiple access (NOMA) technique is employed at each UAV to further improve the spectrum efficiency of the wireless network.
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.
Learning-Based Predictive Control via Real-Time Aggregate Flexibility
To be used effectively, an aggregator must be able to communicate the available flexibility of the loads they control, as known as the aggregate flexibility to a system operator.
Optimization and Control Systems and Control Systems and Control
Deep Learning for Latent Events Forecasting in Twitter Aided Caching Networks
A novel Twitter context aided content caching (TAC) framework is proposed for enhancing the caching efficiency by taking advantage of the legibility and massive volume of Twitter data.
MIMO Assisted Networks Relying on Intelligent Reflective Surfaces
The network's SE and EE are also derived.
Information Theory Signal Processing Information Theory
DCT and DST Filtering with Sparse Graph Operators
These sparse operators can be viewed as graph filters operating in the DCT domain, which allows us to approximate any DCT graph filter by a MPGF, leading to a design with more degrees of freedom than the conventional PGF approach.
Integrated 3C in NOMA-enabled Remote-E-Health Systems
A novel framework is proposed to integrate communication, control and computing (3C) into the fifth-generation and beyond (5GB) wireless networks for satisfying the ultra-reliable low-latency connectivity requirements of remote-e-Health systems.
Artificial Intelligence Driven UAV-NOMA-MEC in Next Generation Wireless Networks
To this end, the fundamentals of this framework are first introduced.
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.
Machine Learning Empowered Trajectory and Passive Beamforming Design in UAV-RIS Wireless Networks
The energy consumption minimizing problem is formulated by jointly designing the movement of the UAV, phase shifts of the RIS, power allocation policy from the UAV to MUs, as well as determining the dynamic decoding order.
Storage and Transmission Capacity Requirements of a Remote Solar Power Generation System
Large solar power stations usually locate in remote areas and connect to the main grid via a long transmission line.
Hallucinated Neural Radiance Fields in the Wild
This paper studies the problem of hallucinated NeRF: i. e., recovering a realistic NeRF at a different time of day from a group of tourism images.
A New Look at AI-Driven NOMA-F-RANs: Features Extraction, Cooperative Caching, and Cache-Aided Computing
Non-orthogonal multiple access (NOMA) enabled fog radio access networks (NOMA-F-RANs) have been taken as a promising enabler to release network congestion, reduce delivery latency, and improve fog user equipments' (F-UEs') quality of services (QoS).
Dynamic Flow Equilibrium of Transportation and Power Distribution Networks Considering Flexible Traveling Choices and Voltage Quality Improvement
The increasing global spread of electric vehicles (EVs) has introduced significant interdependence between transportation and power networks.
Towards Transactive Energy: An Analysis of Information-related Practical Issues
The development of distributed energy resources, such as rooftop photovoltaic (PV) panels, batteries, and electric vehicles (EVs), has decentralized our power system operation, where transactive energy markets empower local energy exchanges.
Smart Director: An Event-Driven Directing System for Live Broadcasting
To our best knowledge, our system is the first end-to-end automated directing system for multi-camera sports broadcasting, completely driven by the semantic understanding of sports events.
Hybrid Reinforcement Learning for STAR-RISs: A Coupled Phase-Shift Model Based Beamformer
Despite the coupled nature of the phase-shift model, the formulated problem is solved by invoking a hybrid continuous and discrete phase-shift control policy.
IUCL at WASSA 2022 Shared Task: A Text-only Approach to Empathy and Emotion Detection
Our system, IUCL, participated in the WASSA 2022 Shared Task on Empathy Detection and Emotion Classification.
Distributed Coordination of Charging Stations Considering Aggregate EV Power Flexibility
However, effective management of charging stations is challenging due to individual EV owners' privacy concerns, competing interests of different stations, and the coupling distribution network constraints.
Zero-shot Cross-Linguistic Learning of Event Semantics
Typologically diverse languages offer systems of lexical and grammatical aspect that allow speakers to focus on facets of event structure in ways that comport with the specific communicative setting and discourse constraints they face.
Distributed Coordination of Charging Stations with Shared Energy Storage in a Distribution Network
Though charging stations can install energy storage to reduce their impacts on the grid, the conventional "one charging station, one energy storage" method may be uneconomical due to the high upfront cost of energy storage.
Landmark Tracking in Liver US images Using Cascade Convolutional Neural Networks with Long Short-Term Memory
We further tested the proposed model on 69 landmarks from the testing dataset that has a similar image pattern to the training pattern, resulting in a mean tracking error of 0. 94+/-0. 83 mm.
Local-to-Global Registration for Bundle-Adjusting Neural Radiance Fields
Neural Radiance Fields (NeRF) have achieved photorealistic novel views synthesis; however, the requirement of accurate camera poses limits its application.
Place Recognition under Occlusion and Changing Appearance via Disentangled Representations
Place recognition is a critical and challenging task for mobile robots, aiming to retrieve an image captured at the same place as a query image from a database.
Sizing Grid-Connected Wind Power Generation and Energy Storage with Wake Effect and Endogenous Uncertainty: A Distributionally Robust Method
In this paper, a bi-objective distributionally robust optimization (DRO) model is proposed to determine the capacities of wind power generation and ESSs considering the wake effect.
t-SMILES: A Scalable Fragment-based Molecular Representation Framework for De Novo Molecule Generation
Effective representation of molecules is a crucial factor affecting the performance of artificial intelligence models.
Automatic Sleep Stage Classification with Cross-modal Self-supervised Features from Deep Brain Signals
This sleep stage classification model could be adapted to chronic and continuous monitor sleep for Parkinson's patients in daily life, and potentially utilized for more precise treatment in deep brain-machine interfaces, such as closed-loop deep brain stimulation.
Approach to Learning Generalized Audio Representation Through Batch Embedding Covariance Regularization and Constant-Q Transforms
Preliminary results show (1) the proposed BECR can incur a more dispersed embedding on the test set, (2) BECR improves the PaSST model without extra computation complexity, and (3) STFT preprocessing outperforms CQT in all tasks we tested.
Latent Semantic Diffusion-based Channel Adaptive De-Noising SemCom for Future 6G Systems
Upon the designed DNSC architecture, we further combine adversarial learning, variational autoencoder, and diffusion model to propose the Latent Diffusion DNSC (Latent-Diff DNSC) scheme to realize intelligent online de-noising.
Hierarchical Game for Coupled Power System with Energy Sharing and Transportation System
This necessitates new business models in the power sector to hedge against uncertainties while imposing a strong coupling between the connected power and transportation networks.
An Overview about Emerging Technologies of Autonomous Driving
Since DARPA started Grand Challenges in 2004 and Urban Challenges in 2007, autonomous driving has been the most active field of AI applications.
Eva-KELLM: A New Benchmark for Evaluating Knowledge Editing of LLMs
In this paper, we propose Eva-KELLM, a new benchmark for evaluating knowledge editing of LLMs.
Stochastic Optimization of Coupled Power Distribution-Urban Transportation Network Operations with Autonomous Mobility on Demand Systems
Then, a bi-level power-traffic flow (PTF) model is proposed to characterize the interaction of power distribution networks (PDNs) and urban transportation networks (UTNs).
Neural Image Compression Using Masked Sparse Visual Representation
A set of semantic-class-dependent basis codebooks are learned, which are weighted combined to generate a rich latent feature for high-quality reconstruction.
A Multi-timescale and Chance-Constrained Energy Dispatching Strategy of Integrated Heat-Power Community with Shared Hybrid Energy Storage
In the integrated heat-power system with coupling heat-power generators and demands, the key challenges lie in the interaction between heat and power, the inherent uncertainty of renewable energy and consumers' demands, and the multi-timescale scheduling of heat and power.
Applications of Large Scale Foundation Models for Autonomous Driving
Since DARPA Grand Challenges (rural) in 2004/05 and Urban Challenges in 2007, autonomous driving has been the most active field of AI applications.
Economic Forces in Stock Returns
Driven by such motivation, we conduct an attribution analysis based on the general framework of their model to further prove the importance of the economic factors and identify the specific identity of significant factors.
Distributed Stackelberg Equilibrium Seeking for Networked Multi-Leader Multi-Follower Games with A Clustered Information Structure
In this case, the leaders cannot fully anticipate the collective rational response of all followers with its local information.
CRISIS ALERT:Forecasting Stock Market Crisis Events Using Machine Learning Methods
Historically, the economic recession often came abruptly and disastrously.
TPLLM: A Traffic Prediction Framework Based on Pretrained Large Language Models
Traffic prediction constitutes a pivotal facet within the purview of Intelligent Transportation Systems (ITS), and the attainment of highly precise predictions holds profound significance for efficacious traffic management.
RLGNet: Repeating-Local-Global History Network for Temporal Knowledge Graph Reasoning
Temporal Knowledge Graph (TKG) reasoning is based on historical information to predict the future.
