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Found 18 papers, 4 papers with code
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.
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.
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.
Distributed Differential Evolution Based on Adaptive Mergence and Split for Large-Scale Optimization
In this way, the number of subpopulations is adaptively adjusted and better performing subpopulations obtain more individuals.
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.
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.
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
A TSK-type Convolutional Recurrent Fuzzy Network for Predicting Driving Fatigue
To effectively predict driving fatigue, this paper proposes a new deep learning framework called TSK-type Convolution Recurrent Fuzzy Network (TCRFN) based on the spatial and temporal characteristics of EEG signals.
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.
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).
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.
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.
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.
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.
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.
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.
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.
