Results 101 to 110 of about 3,557 (290)

Automatic target recognition of aircraft models based on ISAR images

, 2009
In this paper, we present a system for aircraft automatic target recognition (ATR) using Inverse Synthetic Aperture Radar (ISAR) and based on Knowledge discovery from data process adapted to radar domain.
B. Hoeltzener, M. N. Saidi, Daoudi, K., Hoeltzener, Brigitte, A. Khenchaf, Saidi, Mn, Khenchaf, Ali, Aboutajdine, D., D. Aboutajdine, K. Daoudi   +9 more
core   +1 more source

Lidar‐Based Object Tracking of Traffic Participants with Sensor Nodes in Existing Urban Infrastructure

Advanced Intelligent Systems, EarlyView.
This paper presents a lidar‐based sensor node design and a rule‐based state observer for edge‐based traffic participant tracking. Unlike other state‐of‐the‐art methods, this state observer enables real‐time, CPU‐only edge processing without relying on machine learning approaches.
Simon Schäfer, Bassam Alrifaee, Ehsan Hashemi   +2 more
wiley   +1 more source

Concentric Rheostat Decoupled 3D Force‐Sensing Module for Smart Table Tennis Training

Advanced Intelligent Systems, EarlyView.
A 3D‐printed sensor array intrinsically decouples normal and shear forces through a unique concentric structural design. By integrating piezoresistive, sliding area‐varying capacitive, and concentric rheostat mechanisms, the 12‐sensor module achieves high‐resolution 3D force mapping without complex algorithms.
Zhe Liu, Kunlin Wu, Bingrui Sim, Wenjie Lai, Xingyu Chen, Jiajun Liu, Yifan Wang, Soo Jay Phee   +7 more
wiley   +1 more source

Radar HRRP Feature Fusion Recognition Method Based on ConvLSTM Network with Multi-Input Gate Recurrent Unit

Remote Sensing
Recently, the radar high-resolution range profiles (HRRPs) have gained significant attention in the field of radar automatic target recognition due to their advantages of being easy to acquire, having a small data footprint, and providing rich target ...
Wei Yang, Tianqi Chen, Shiwen Lei, Zhiqin Zhao, Haoquan Hu, Jun Hu   +5 more
doaj   +1 more source

Automatic target recognition using passive bistatic radar signals.

Reconnaissance automatique de cibles par utilisation de signaux de radars passifs bistatiques Dans cette thèse, nous présentons la conception, le développement et le test de trois systèmes de reconnaissance automatique de cibles (ATR) visant à reconnaître des avions non-coopératifs, c’est-à-dire des avions ne fournissant par leur ...
openaire   +2 more sources

Robust Automatic Target Recognition Using Extra-trees

, 2010
peer reviewedIn this paper, we describe a new automatic target recognition algorithm for classifying SAR images based on the PiXiT image classifier. It uses randomized sub-windows extraction and extremely randomized trees (extra-trees).
Wehenkel, Louis, Marée, Raphaël, Jacques Verly, Louis Wehenkel, Jonathan Pisane, Raphael Maree, Verly, Jacques, Pisane, Jonathan   +7 more
core   +1 more source

ParamNet: A Physics‐Guided Deep Learning Framework for Intelligent Self‐Inversion of Vacuum Optical Levitation Systems

Advanced Intelligent Systems, EarlyView.
A physics‐guided deep learning framework, ParamNet, is introduced for the intelligent self‐inversion of vacuum optical tweezers. By fuzing dual‐branch time–frequency features with physical dynamical constraints, it achieves high‐accuracy calibration of trap parameters from short‐window, low‐frequency trajectories, outperforming traditional methods ...
Qi Zheng, Wenfeng Fan, Feng Li, Jian Wu, Wei Quan   +4 more
wiley   +1 more source

SAR automatic target recognition based on deep convolutional neural network

, 2017
In the past years, researchers have shown more and more interests in synthetic aperture radar (SAR) automatic target recognition (ATR), and many methods have been proposed and studied for radar target recognition.
Ying Xu, Fabio Scotti, J. Liu, Vincenzo Piuri, K. Liu, Kaipin Liu, Z. Ying, Lijuan Shang, Jian Liu, Yikui Zhai, Zilu Ying, L. Shang, Y. Xu, Y. Zhai, V. Piuri, F. Scotti   +15 more
core   +1 more source

Interpreting How Neural Networks Infer Scatterer Geometry from Echolocation Echoes

Advanced Intelligent Systems, EarlyView.
Neural networks enable echolocation‐based shape classification but remain difficult to interpret due to their black‐box nature. This work presents a feature‐importance metric to uncover the echo regions driving decisions in shape‐specialized networks.
Ganesh U. Patil, Hyung‐Suk Kwon, Bogdan‐Ioan Popa   +2 more
wiley   +1 more source

A Residual Optronic Convolutional Neural Network for SAR Target Recognition

Photonics
Deep learning (DL) has shown great capability in remote sensing and automatic target recognition (ATR). However, huge computational costs and power consumption are challenging the development of current DL methods.
Ziyu Gu, Zicheng Huang, Xiaotian Lu, Hongjie Zhang, Hui Kuang   +4 more
doaj   +1 more source