Results 11 to 20 of about 11,848 (250)

A Robust Multi-Sensor Data Fusion Clustering Algorithm Based on Density Peaks

Sensors, 2019
In this paper, a novel multi-sensor clustering algorithm, based on the density peaks clustering (DPC) algorithm, is proposed to address the multi-sensor data fusion (MSDF) problem.
Jiande Fan, Weixin Xie, Haocui Du
doaj   +1 more source

One-vs-All Convolutional Neural Networks for Synthetic Aperture Radar Target Recognition

Cybernetics and Information Technologies, 2022
Convolutional Neural Networks (CNN) have been widely utilized for Automatic Target Recognition (ATR) in Synthetic Aperture Radar (SAR) images. However, a large number of parameters and a huge training data requirements limit CNN’s use in SAR ATR.
Babu Bileesh Plakkal, Narayanan Swathi Jamjala   +1 more
doaj   +1 more source

Automatic recognition of military vehicles with Krawtchouk moments [PDF]

, 2016
The challenge of Automatic Target Recognition (ATR) of military targets within a Synthetic Aperture Radar (SAR) scene is addressed in this paper. The proposed approach exploits the discrete defined Krawtchouk moments, that are able to represent a ...
Clemente, Carmine, De Maio, Antonio, Gaglione, Domenico, Pallotta, Luca, Soraghan, John J.   +4 more
core   +1 more source

A Novel FEM Based T-S Fuzzy Particle Filtering for Bearings-Only Maneuvering Target Tracking

Sensors, 2019
In this paper, we propose a novel fuzzy expectation maximization (FEM) based Takagi-Sugeno (T-S) fuzzy particle filtering (FEMTS-PF) algorithm for a passive sensor system.
Xiaoli Wang, Liangqun Li, Weixin Xie
doaj   +1 more source

Fusing Deep Learning and Sparse Coding for SAR ATR [PDF]

, 2018
We propose a multimodal and multidiscipline data fusion strategy appropriate for automatic target recognition (ATR) on synthetic aperture radar imagery. Our architecture fuses a proposed clustered version of the AlexNet convolutional neural network with ...
Aouf, N., Kechagias-Stamatis, O.
core   +2 more sources

When Deep Learning Meets Multi-Task Learning in SAR ATR: Simultaneous Target Recognition and Segmentation

Remote Sensing, 2020
With the recent advances of deep learning, automatic target recognition (ATR) of synthetic aperture radar (SAR) has achieved superior performance.
Chenwei Wang, Jifang Pei, Zhiyong Wang, Yulin Huang, Junjie Wu, Haiguang Yang, Jianyu Yang   +6 more
doaj   +1 more source

Real-Time Underwater Maritime Object Detection in Side-Scan Sonar Images Based on Transformer-YOLOv5

Remote Sensing, 2021
To overcome the shortcomings of the traditional manual detection of underwater targets in side-scan sonar (SSS) images, a real-time automatic target recognition (ATR) method is proposed in this paper. This method consists of image preprocessing, sampling,
Yongcan Yu, Jianhu Zhao, Quanhua Gong, Chao Huang, Gen Zheng, Jinye Ma   +5 more
doaj   +1 more source

A Channelization-Based DOA Estimation Method for Wideband Signals

Sensors, 2016
In this paper, we propose a novel direction of arrival (DOA) estimation method for wideband signals with sensor arrays. The proposed method splits the wideband array output into multiple frequency sub-channels and estimates the signal parameters using a ...
Rui Guo, Yue Zhang, Qianqiang Lin, Zengping Chen   +3 more
doaj   +1 more source

An Integrated Counterfactual Sample Generation and Filtering Approach for SAR Automatic Target Recognition with a Small Sample Set

Remote Sensing, 2021
Although automatic target recognition (ATR) models based on data-driven algorithms have achieved excellent performance in recent years, the synthetic aperture radar (SAR) ATR model often suffered from performance degradation when it encountered a small ...
Changjie Cao, Zongyong Cui, Zongjie Cao, Liying Wang, Jianyu Yang   +4 more
doaj   +1 more source

Local feature based automatic target recognition for future 3D active homing seeker missiles [PDF]

, 2017
We propose an architecture appropriate for future Light Detection and Ranging (LIDAR) active homing seeker missiles with Automatic Target Recognition (ATR) capabilities.
Aouf, N., Chermak, L., Gray, G., Kechagias-Stamatis, O., Oudyi, F., Richardson, M.   +5 more
core   +3 more sources