Search Results for author:
Found 15 papers, 2 papers with code
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.
Coverage Control Algorithm for DSNs Based on Improved Gravitational Search
—In directional sensor networks (DSNs), coverage control is an important way to ensure efficient communication and reliable data transmission.
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).
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).
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
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.
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.
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.
A MIP Model for Risk Constrained Switch Placement in Distribution Networks
The model is applied to the RBTS-Bus4 and a real distribution network.
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.
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 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.
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)
Automatic Parameter Selection for Denoising Algorithms Using a No-Reference Measure of Image Content
Across the field of inverse problems in image and video processing, nearly all algorithms have various parameters which need to be set in order to yield good results.
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.
