Search Results for author:
Found 49 papers, 7 papers with code
Instance Paradigm Contrastive Learning for Domain Generalization
In this paper, we propose an instance paradigm contrastive learning framework, introducing contrast between original features and novel paradigms to alleviate domain-specific distractions.
An Ultralightweight Hybrid CNN Based on Redundancy Removal for Hyperspectral Image Classification
Simultaneously, for PW-Conv, we design a spectral convolution with redundancy removal (R2Spectral-Conv).
Meta Reinforcement Learning for Multi-Task Offloading in Vehicular Edge Computing
The objective is to design a unified solution to minimize task execution time under different MTO scenarios.
Ultra-Robust Real-Time Estimation of Gait Phase
The estimator is finally tested on a participant walking with an active exoskeleton, demonstrating the robustness of D67 in interaction with an exoskeleton without being trained on any data from the test subject with or without an exoskeleton.
Interaction-Aware Planning With Deep Inverse Reinforcement Learning for Human-Like Autonomous Driving in Merge Scenarios
To consider the interaction factor, the reward function for planning is utilized to evaluate the joint trajectories of the autonomous driving vehicle (ADV) and traffic vehicles.
Spoof Trace Disentanglement for generic face antispoofing
Yet, it is a challenging task due to the diversity of spoof attacks and the lack of ground truth for spoof traces.
Bio-Inspired Feature Selection in Brain Disease Detection via an Improved Sparrow Search Algorithm
Finally, the proposed ISSA is utilized to solve the objective function.
VCI-LSTM: Vector Choquet Integral-based Long Short-Term Memory
Choquet integral is a widely used aggregation oper- ator on one-dimensional and interval-valued information, since it is able to take into account the possible interaction among data.
Lightweight Deep Neural Network for Joint Learning of Underwater Object Detection and Color Conversion
Li-Wei Kang is with the Department of Electrical Engineering, National Taiwan Normal University, Taipei 106, Taiwan (e-mail: lwkang@ntnu. edu. tw).
Topology Change Aware Data-Driven Probabilistic Distribution State Estimation Based on Gaussian Process
Abstract—This paper addresses the distribution system state estimation (DSSE) with unknown topology change.
STMGCN: Mobile Edge Computing-Empowered Vessel Trajectory Prediction Using Spatio-Temporal Multigraph Convolutional Network
—The revolutionary advances in machine learning and data mining techniques have contributed greatly to the rapid developments of maritime Internet of Things (IoT).
Deep Reinforcement Learning based Model-free On-line Dynamic Multi-Microgrid Formation to Enhance Resilience
The proposed deep RL method provides real-time computing to support on-line dynamic MMGF scheme, and the scheme handles a long-term resilience enhancement problem using adaptive on-line MMGF to defend changeable conditions.
High-order Correlation Preserved Incomplete Multi-view Subspace Clustering
Specifically, multiple affinity matrices constructed from the incomplete multi-view data are treated as a thirdorder low rank tensor with a tensor factorization regularization which preserves the high-order view correlation and sample correlation.
A GAN-Based Short-Term Link Traffic Prediction Approach for Urban Road Networks Under a Parallel Learning Framework
This paper proposes a short-term traffic speed prediction approach, called PL-WGAN, for urban road networks, which is considered an important part of a novel parallel learning framework for traffic control and operation.
Shallow Network Based on Depthwise Over-Parameterized Convolution for Hyperspectral Image Classification
Therefore, this letter proposes a shallow model for HSIC, which is called depthwise over-parameterized convolutional neural network (DOCNN).
Double Deep Q-learning Based Real-Time Optimization Strategy for Microgrids
It is challenging to solve this kind of stochastic nonlinear optimization problem.
Deep Learning Based Autonomous Vehicle Super Resolution DOA Estimation for Safety Driving
Abstract— In this paper, a novel system architecture including a massive multi-input multi-output (MIMO) or a reconfigurable intelligent surface (RIS) and multiple autonomous vehicles is considered in vehicle location systems.
Content-Preserving Image Stitching with Piecewise Rectangular Boundary Constraints
By analyzing the irregular boundary, we construct a piecewise rectangular boundary.
Detailed Primary and Secondary Distribution System Model Enhancement Using AMI Data
Reliable and accurate distribution system modeling, including the secondary network, is essential in examining distribution system performance with high penetration of distributed energy resources (DERs).
Context-aware taxi dispatching at city-scale using deep reinforcement learning
Abstract— Proactive taxi dispatching is of great importance to balance taxi demand-supply gaps among different locations in a city.
Multi-Scale and Multi-Direction GAN for CNN-Based Single Palm-V ein Identification
Despite recent advances of deep neural networks in hand vein identification, the existing solutions assume the availability of a large and rich set of training image samples.
Data-Driven Assisted Chance-Constrained Energy and Reserve Scheduling with Wind Curtailment
Case studies performed on the PJM 5-bus and IEEE 118-bus systems demonstrate that the proposed method is capable of accurately accounting the influence of wind curtailment dispatch in CCO.
Systems and Control Systems and Control
CRPN-SFNet: A High-Performance Object Detector on Large-Scale Remote Sensing Images
Extensive experiments on the public Dataset for Object deTection in Aerial images data set indicate that our CRPN can help our detector deal the larger image faster with the limited GPU memory; meanwhile, the SFNet is beneficial to achieve more accurate detection of geospatial objects with wide-scale range.
Completion of Missing Labels for Multi-Label Annotation by a Unified Graph Laplacian Regularization
This work proposes a novel method to solve the problem of multi-label image annotation by unifying two different types of Laplacian regularization terms in deep convolutional neural network (CNN) for robust annotation performance.
Frame-wise Cross-modal Matching for Video Moment Retrieval
Another contribution is that we propose an additional predictor to utilize the internal frames in the model training to improve the localization accuracy.
Attention Transfer Network for Nature Image Matting
Then, we introduce a scale transfer block to magnify the feature maps without adding extra information.
A New Multiple Source Domain Adaptation Fault Diagnosis Method between Different Rotating Machines
To solve this issue, transfer learning is proposed by leveraging knowl- edge learned from source domain to target domain.
Edge server deployment scheme of blockchain in IoVs
In fact, the application of blockchain in IoVs can be implemented by employing edge computing.
Service Provisioning Framework for RAN Slicing: User Admissibility, Slice Association and Bandwidth Allocation
Network slicing (NS) has been identified as one of the most promising architectural technologies for future mobile network systems to meet the extremely diversified service requirements of users.
Decision Fusion in Space-Time Spreading aided Distributed MIMO WSNs
In this letter, we propose space-time spreading (STS) of local sensor decisions before reporting them over a wireless multiple access channel (MAC), in order to achieve flexible balance between diversity and multiplexing gain as well as eliminate any chance of intrinsic interference inherent in MAC scenarios.
A Lightweight and Privacy-Preserving Authentication Protocol for Mobile Edge Computing
With the advent of the Internet-of-Things (IoT), vehicular networks and cyber-physical systems, the need for realtime data processing and analysis has emerged as an essential pre-requite for customers’ satisfaction.
Reconfigurable Intelligent Surface Assisted Multiuser MISO Systems Exploiting Deep Reinforcement Learning
In this paper, we investigate the joint design of transmit beamforming matrix at the base station and the phase shift matrix at the RIS, by leveraging recent advances in deep reinforcement learning (DRL).
Reinforcement Learning Tracking Control for Robotic Manipulator With Kernel-Based Dynamic Model
In this algorithm, a reward function is defined according to the features of tracking control in order to speed up the learning process, and then an RL tracking controller with a kernel-based transition dynamic model is proposed.
Broad Learning System Based on Maximum Correntropy Criterion
As an effective and efficient discriminative learning method, Broad Learning System (BLS) has received increasing attention due to its outstanding performance in various regression and classification problems.
Localization and Clustering Based on Swarm Intelligence in UAV Networks for Emergency Communications
Second, we propose an energy-efficient swarm-intelligence-based clustering (SIC) algorithm based on PSO, in which the particle fitness function is exploited for inter-cluster distance, intra-cluster distance, residual energy, and geographic location.
A Universal Approximation Result for Difference of log-sum-exp Neural Networks
We show that a neural network whose output is obtained as the difference of the outputs of two feedforward networks with exponential activation function in the hidden layer and logarithmic activation function in the output node (LSE networks) is a smooth universal approximator of continuous functions over convex, compact sets.
Discrete-Time Impulsive Adaptive Dynamic Programming
Abstract—In this paper, a new iterative adaptive dynamic programming (ADP) algorithm is developed to solve optimal impulsive control problems for infinite horizon discrete-time nonlinear systems.
A MIP Model for Risk Constrained Switch Placement in Distribution Networks
The model is applied to the RBTS-Bus4 and a real distribution network.
PEA265: Perceptual Assessment of Video Compression Artifacts
To monitor and improve visual QoE, it is crucial to develop subjective and objective measures that can identify and quantify various types of PEAs.
Blockchain for Secure and Efficient Data Sharing in Vehicular Edge Computing and Networks
Due to limited resources with vehicles, vehicular edge computing and networks (VECONs) i. e., the integration of mobile edge computing and vehicular networks, can provide powerful computing and massive storage resources.
Optimal Training for Residual Self-Interference for Full-Duplex One-Way Relays
For the former, we propose a training scheme to estimate the overall channel, and for the latter the CRB and the optimal number of relays are derived when the distance between the source and the destination is fixed.
Robust Single Image Super-Resolution via Deep Networks With Sparse Prior
We demonstrate that a sparse coding model particularly designed for SR can be incarnated as a neural network with the merit of end-to-end optimization over training data.
Distributed Consensus-Based Economic Dispatch With Transmission Losses
The second algorithm performs the estimation ofthe power mismatch in the system using a consensus strategy called consensus on the most up-to-date information.
A Decentralized Cooperative Control Scheme With Obstacle Avoidance for a Team of Mobile Robots
The problem of formation control of a team of mobile robots based on the virtual and behavioral structures is considered in this paper.
A Grid-Based Evolutionary Algorithm for Many-Objective Optimization
Balancing convergence and diversity plays a key role in evolutionary multiobjective optimization (EMO).
Physiological Parameter Monitoring from Optical Recordings with a Mobile Phone
We show that a mobile phone can serve as an accurate monitor for several physiological variables, based on its ability to record and analyze the varying color signals of a fingertip placed in contact with its optical sensor.
Ranked #1 on
SpO2 estimation
on Video recordings of fingertip under mobile phone fla
(using extra training data)
Performance Analysis of Two Hop Amplify-and-Forward Systems with Interference at the Relay
Abstract—We analyze the performance of a two hop channel state information (CSI)-assisted amplify-and-forward system, with co-channel interference at the relay.
Efficiently Indexing Large Sparse Graphs for Similarity Search
Abstract—The graph structure is a very important means to model schemaless data with complicated structures, such as protein- protein interaction networks, chemical compounds, knowledge query inferring systems, and road networks.
ANALYSIS OF CALIBRATED SEA CLUTTER AND BOAT REFLECTIVITY DATA AT C- AND X-BAND IN SOUTH AFRICAN COASTAL WATERS
Abstract—The synthesis-based sparse representation model for signals has drawn considerable interest in the past decade.
