Results 61 to 70 of about 48,420 (287)
Using Classify-While-Scan (CWS) Technology to Enhance Unmanned Air Traffic Management (UTM)
Drones, 2022 Drone detection radar systems have been verified for supporting unmanned air traffic management (UTM). Here, we propose the concept of classify while scan (CWS) technology to improve the detection performance of drone detection radar systems and then to ...
Jiangkun Gong +4 more
doaj +1 more source
Radar HRRP Modeling using Dynamic System for Radar Target Recognition [PDF]
, 2014 High resolution range profile (HRRP) is being known as one of the most powerful tools for radar target recognition. The main problem with range profile for radar target recognition is its sensitivity to aspect angle. To overcome this problem, consecutive
Ajorloo, A. +3 more
core
A Multiple Migration and Stacking Algorithm Designed for Land Mine Detection [PDF]
, 2014 This paper describes a modification to a standard migration algorithm for land mine detection with a ground-penetrating radar (GPR) system. High directivity from the antenna requires a significantly large aperture in relation to the operating wavelength,
Daniels, David +2 more
core +1 more source
CARRADA Dataset: Camera and Automotive Radar with Range-Angle-Doppler Annotations
, 2021 High quality perception is essential for autonomous driving (AD) systems. To reach the accuracy and robustness that are required by such systems, several types of sensors must be combined. Currently, mostly cameras and laser scanners (lidar) are deployed
Newson, A. +4 more
core +3 more sources
Advanced Materials, EarlyView.The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj +8 more
wiley +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 +1 more
doaj +1 more source
Radar Target Recognition by Convolutional Capsule Networks Based on High-Resolution Range Profile
IEEE Access, 2022 Automatic target recognition (ATR) is of increasing importance for the modern radar system, where the high-resolution range profile (HRRP) is essential.
Xianwen Zhang +3 more
doaj +1 more source
A Scalable Perovskite Platform With Multi‐State Photoresponsivity for In‐Sensor Saliency Detection
Advanced Materials, EarlyView.A scalable in‐sensor computing platform (32 × 32 array) with ultra‐low variability is developed by incorporating ferroelectric copolymers into halide perovskite thin films. These devices achieve 1000 programmable photoresponsivity states and high thermal reliability.
Xuechao Xing +10 more
wiley +1 more source
Remote Sensing, 2018 The algorithm of synthetic aperture radar (SAR) for automatic target recognition consists of two stages: feature extraction and classification. The quality of extracted features has significant impacts on the final classification performance.
Haipeng Wang +3 more
doaj +1 more source
Deep learning in remote sensing: a review [PDF]
, 2017 Standing at the paradigm shift towards data-intensive science, machine learning techniques are becoming increasingly important. In particular, as a major breakthrough in the field, deep learning has proven as an extremely powerful tool in many fields ...
Fraundorfer, Friedrich +6 more
core +4 more sources