Results 51 to 60 of about 824,134 (332)

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

Classifying objects in LWIR imagery via CNNs [PDF]

, 2016
The aim of the presented work is to demonstrate enhanced target recognition and improved false alarm rates for a mid to long range detection system, utilising a Long Wave Infrared (LWIR) sensor.
Connor, Barry, Robertson, Neil M., Rodger, Iain   +2 more
core   +1 more source

ATGAN: A SAR Target Image Generation Method for Automatic Target Recognition

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
The performance of a deep learning-based synthetic aperture radar (SAR) automatic target recognition (ATR) model largely relies on the scale and quality of training samples.
Zhiqiang Zeng, Xiaoheng Tan, Xin Zhang, Yan Huang, Jun Wan, Zhanye Chen   +5 more
semanticscholar   +1 more source

Automatic Target Recognition for Low Resolution Foliage Penetrating SAR Images Using CNNs and GANs

Remote Sensing, 2021
In recent years, the technological advances leading to the production of high-resolution Synthetic Aperture Radar (SAR) images has enabled more and more effective target recognition capabilities. However, high spatial resolution is not always achievable,
D. Vint, Matthew O. Anderson, Yuhao Yang, C. Ilioudis, G. D. Caterina, C. Clemente   +5 more
semanticscholar   +1 more source

Geospatial Object Detection in Remote Sensing Imagery Based on Multiscale Single-Shot Detector with Activated Semantics

Remote Sensing, 2018
Geospatial object detection from high spatial resolution (HSR) remote sensing imagery is a heated and challenging problem in the field of automatic image interpretation.
Shiqi Chen, Ronghui Zhan, Jun Zhang
doaj   +1 more source

Arbitrary clutter extended target probability hypothesis density filter

IET Radar, Sonar & Navigation, 2021
Based on the random finite set (RFS) framework and the probability hypothesis density (PHD) filter, the extended target PHD (ET‐PHD) filter is proposed for multiple extended target tracking.
Xinglin Shen, Luping Zhang, Moufa Hu, Shanzhu Xiao, Huamin Tao   +4 more
doaj   +1 more source

Multilingual extension of a temporal expression normalizer using annotated corpora [PDF]

, 2006
This paper presents the automatic extension to other languages of TERSEO, a knowledge-based system for the recognition and normalization of temporal expressions originally developed for Spanish.
Martínez-Barco, Patricio, Muñoz, Rafael, Negri, Matteo, Saquete Boró, Estela, Speranza, Manuela, Sprugnoli, Rachele   +5 more
core   +1 more source

Multiscale Complex-Valued Feature Attention Convolutional Neural Network for SAR Automatic Target Recognition

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Synthetic aperture radar (SAR) images often lack sufficient attention to target features, inadequately express target feature information, and neglect phase information in conventional Convolutional Neural Network (CNN) recognition methods.
Xiaoqian Zhou, Cai Luo, P. Ren, Bin Zhang   +3 more
semanticscholar   +1 more source

Low-Rank and Sparse Matrix Decomposition with Cluster Weighting for Hyperspectral Anomaly Detectiond

Remote Sensing, 2018
Hyperspectral anomaly detection plays an important role in the field of remote sensing. It provides a way to distinguish interested targets from the background without any prior knowledge. The majority of pixels in the hyperspectral dataset belong to the
Lingxiao Zhu, Gongjian Wen, Shaohua Qiu
doaj   +1 more source

Few Shot Object Detection for SAR Images via Feature Enhancement and Dynamic Relationship Modeling

Remote Sensing, 2022
Current Synthetic Aperture Radar (SAR) image object detection methods require huge amounts of annotated data and can only detect the categories that appears in the training set.
Shiqi Chen, Jun Zhang, Ronghui Zhan, Rongqiang Zhu, Wei Wang   +4 more
doaj   +1 more source