Results 51 to 60 of about 1,725,722 (217)

Study on feature processing schemes for deep‐learning‐based human activity classification using frequency‐modulated continuous‐wave radar

IET Radar, Sonar & Navigation, 2021
Radar is an attractive sensor for classifying human activity because of its invariance to the environment and its ability to operate under low lighting conditions and through obstacles.
Rodrigo Hernangómez, Avik Santra, Sławomir Stańczak   +2 more
doaj   +1 more source

IAA-Based Radar Micro-Doppler Signatures of Human Activities [PDF]

Micro-Doppler signatures using STFT and ...
Shah, Syed Aziz, Akaydin, Abdullah, Fioranelli, Francesco, Yang, Shufan, Shrestha, Aman, Le Kernec, Julien, Li, Zhenghui, Li, Haobo   +7 more
core   +1 more source

Review of CFD modelling techniques for single‐phase and multiphase flow in static mixers

The Canadian Journal of Chemical Engineering, EarlyView.
This review synthesizes computational fluid dynamics (CFD) approaches for static mixers, linking hydrodynamics to pressure drop, particle/droplet distributions, mixing metrics, and heat‐transfer performance to guide modelling choices and design decisions. Abstract Static mixers enable compact and low‐energy intensification.
Jussan Jaeger, Sálvio Lima de Carvalho Neto, Silvio Edegar Weschenfelder, Glaucia Rodrigues Vieira de Almeida da Fonseca, Maria de Fátima Rodrigues da Cunha, Selene Maria Arruda Guelli Ulson de Souza, Evandro Balestrin, Adriano da Silva   +7 more
wiley   +1 more source

Channel Attention based CNN for Improving UAV Classification using Micro Doppler Spectogram Images.

ELCVIA Electronic Letters on Computer Vision and Image Analysis
The increase in technological advancements in unmanned ariel vehicle has lead to the challenges in the detection of drones in flight. The micro Doppler signatures obtained from radars is used to distinguish and detect different types of drones.
Mainak Bandyopadhyay, Suddhasattwa Das, Subhankar Mishra   +2 more
doaj   +1 more source

Three‐dimensional Doppler‐associated radar imaging method based on bi‐directional data processing

IET Radar, Sonar & Navigation, 2022
Using a microwave or millimetre wave radar system, this study aims to achieve highly accurate Doppler velocity estimation and radar imaging that would be suitable for various remote‐sensing sensors, such as self‐driving, surveillance, or security ...
Takumi Hayashi, Takeru Ando, Shouhei Kidera   +2 more
doaj   +1 more source

Flexible wearable electronics for cardiovascular monitoring from surface signals to deep physiological insights

FlexMat, EarlyView.
This review organizes flexible wearable electronics for cardiovascular monitoring into four interconnected information layers: surface electrophysiology, hemodynamic sensing, vascular imaging, and biofluid biomarker analysis. This framework clarifies how electrical rhythm, vascular loading, structural and flow‐related features, and biochemical states ...
Qiao Chen, Hongwen Chen, Yuanyuan Li, Pingan Yang, Rui Li, Zhihao Zhou   +5 more
wiley   +1 more source

Generative Adversarial Networks for Classification of Micro-Doppler Signatures of Human Activity

, 2020
We propose using generative adversarial networks (GANs) for the classification of micro-Doppler signatures measured by the radar. Despite Deep Convolutional Neural Networks (DCNNs) having been used extensively in radar image classification in recent ...
Alnujaim, Ibrahim, Oh, Daegun, Kim, Youngwook   +2 more
core   +1 more source

Strain and Shear Wave Elastography in Thyroid Nodules: Tissue Stiffness as a Complementary Risk Marker for Differentiating Benign, Indeterminate, and Malignant Cytology

Head &Neck, EarlyView.
ABSTRACT Objective To evaluate the diagnostic performance of shear wave elastography (SWE) and strain elastography (SE) as complementary techniques to conventional B‐mode ultrasound for differentiating benign, indeterminate, and malignant thyroid nodules. Methods This prospective cross‐sectional study included 208 thyroid nodules evaluated using B‐mode
Kairo Alexandre Alves Silveira, Icleia Siqueira Barreto, Ilka Mara Borges Botelho, Elizabeth João Pavin, Ademar Yamanaka, Denise Engelbrecht Zantut‐Wittmann   +5 more
wiley   +1 more source

Semisupervised Human Activity Recognition With Radar Micro-Doppler Signatures

IEEE Transactions on Geoscience and Remote Sensing, 2022
Human activity recognition (HAR) plays a vital role in many applications, such as surveillance, in-home monitoring, and health care. Portable radar sensor has been increasingly used in HAR systems in combination with deep learning (DL). However, it is both difficult and time-consuming to obtain a large-scale radar dataset with reliable labels ...
Xinyu Li 0007, Yuan He 0009, Francesco Fioranelli, Xiaojun Jing   +3 more
openaire   +4 more sources

Radar target micro-doppler signature classification [PDF]

, 2008
This thesis reports on research into the field of Micro-Doppler Signature (μ-DS) based radar Automatic Target Recognition (ATR) with additional contributions to general radar ATR methodology.
Smith, G.E.
core