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Found 50 papers, 8 papers with code
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).
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.
Incomplete multi-view clustering
Multi-view Subspace Clustering
+1
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.
A Novel Deep Learning Method for Thermal to Annotated Thermal-Optical Fused Images
As a part of this work, we also present a new and unique database for obtaining the region of interest in thermal images based on an existing thermal visual paired database, containing the Region of Interest on 5 different classes of data.
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.
Deep Reinforcement Learning Based Optimization for IRS Based UAV-NOMA Downlink Networks
This paper investigates the application of deep deterministic policy gradient (DDPG) to intelligent reflecting surface (IRS) based unmanned aerial vehicles (UAV) assisted non-orthogonal multiple access (NOMA) downlink networks.
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.
Low-Complexity Symbol Detection and Interference Cancellation for OTFS System
Orthogonal time frequency space (OTFS) is a two-dimensional modulation scheme realized in the delay- Doppler domain, which targets the robust wireless transmissions in high-mobility environments.
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.
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.
Learning Person Re-identification Models from Videos with Weak Supervision
In order to cope with this issue, we introduce the problem of learning person re-identification models from videos with weak supervision.
Multiple Instance Learning
Video-Based Person Re-Identification
Obstacle Avoidance and Tracking Control of Redundant Robotic Manipulator: An RNN-Based Metaheuristic Approach
In this article, we present a metaheuristic-based control framework, called beetle antennae olfactory recurrent neural network, for simultaneous tracking control and obstacle avoidance of a redundant manipulator.
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.
A Simplified 2D-3D CNN Architecture for Hyperspectral Image Classification Based on Spatial–Spectral Fusion
Abstract—Convolutional neural networks (CNN) have led to a successful breakthrough for hyperspectral image classification (HSIC).
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.
Energy-Efficient Over-the-Air Computation Scheme for Densely Deployed IoT Networks
The proposed MMSE estimator provides a signif- icant mean squared error improvement with reducing en- ergy consumption compared to the conventional estimator.
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.
GETNET: A General End-to-end Two-dimensional CNN Framework for Hyperspectral Image Change Detection
In order to better handle high dimension problem and explore abundance information, this paper presents a General End-to-end Two-dimensional CNN (GETNET) framework for hyperspectral image change detection (HSI-CD).
VSSA-NET: Vertical Spatial Sequence Attention Network for Traffic Sign Detection
Our contributions are as follows: 1) We propose a multi-resolution feature fusion network architecture which exploits densely connected deconvolution layers with skip connections, and can learn more effective features for the small size object; 2) We frame the traffic sign detection as a spatial sequence classification and regression task, and propose a vertical spatial sequence attention (VSSA) module to gain more context information for better detection performance.
Generalization of the Dark Channel Prior for Single Image Restoration
Abstract— Images degraded by light scattering and absorption, such as hazy, sandstorm, and underwater images, often suffer color distortion and low contrast because of light traveling through turbid media.
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.
A Provably Secure and Efficient Identity-Based Anonymous Authentication Scheme for Mobile Edge Computing
Mobile edge computing (MEC) allows one to overcome a number of limitations inherent in cloud computing, although achieving the broad range of security requirements in MEC settings remains challenging.
Location-Centered House Price Prediction: A Multi-Task Learning Approach
Regarding the choice of prediction model, we observe that a variety of approaches either consider the entire house data for modeling, or split the entire data and model each partition independently.
DATS: Dispersive Stable Task Scheduling in Heterogeneous Fog Networks
Abstract—Fog computing has risen as a promising architecture for future Internet of Things (IoT), 5G and embedded artificial intelligence (AI) applications with stringent service delay requirements along the cloud to things continuum.
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.
Medical Image Synthesis with Deep Convolutional Adversarial Networks
To better model a nonlinear mapping from source to target and to produce more realistic target images, we propose to use the adversarial learning strategy to better model the FCN.
Single Image Dehazing Using Color Ellipsoid Prior
The proposed method constructs color ellipsoids that are statistically fitted to haze pixel clusters in RGB space and then calculates the transmission values through color ellipsoid geometry.
Significantly Fast and Robust Fuzzy C-MeansClustering Algorithm Based on MorphologicalReconstruction and Membership Filtering
However, the introduction oflocal spatial information often leads to a high computationalcomplexity, arising out of an iterative calculation of the distancebetween pixels within local spatial neighbors and clusteringcenters.
An Integrated Platform for Live 3D Human Reconstruction and Motion Capturing
The latest developments in 3D capturing, processing, and rendering provide means to unlock novel 3D application pathways.
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.
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)
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.
Parameter-free Geometric Document Layout Analysis
Based on the proposed periodicity measure, multiscale analysis, and confirmation procedure, we could develop a robust method for geometric document layout analysis independent of character font sizes, text line spacing, and document layout structures.
