Results 31 to 40 of about 1,559 (184)

Arm Motion Classification Using Time-Series Analysis of the Spectrogram Frequency Envelopes

Remote Sensing, 2020
Hand and arm gesture recognition using radio frequency (RF) sensing modality proves valuable in man−machine interfaces and smart environments. In this paper, we use the time-series analysis method to accurately measure the similarity of the micro ...
Zhengxin Zeng, Moeness G. Amin, Tao Shan   +2 more
doaj   +1 more source

Attention‐enhanced Alexnet for improved radar micro‐Doppler signature classification

IET Radar, Sonar & Navigation, 2023
This work introduces an attention mechanism that can be integrated into any standard convolution neural network to improve model sensitivity and prediction accuracy with minimal computational overhead.
Shelly Vishwakarma, Wenda Li, Chong Tang, Karl Woodbridge, Ravi Raj Adve, Kevin Chetty   +5 more
doaj   +1 more source

Classification of UAV-to-Ground Vehicles Based on Micro-Doppler Signatures Using Singular Value Decomposition and Deep Convolutional Neural Networks

IEEE Access, 2019
Attack from the unmanned aerial vehicles (UAVs) has been the main means of high-precision strike. Therefore, classifying ground vehicles from the UAV with high accuracy is of great significance.
Lingzhi Zhu, Shuning Zhang, Huichang Zhao, Si Chen, Dongxu Wei, Xiangyu Lu   +5 more
doaj   +1 more source

A 1D Cascaded Denoising and Classification Framework for Micro-Doppler-Based Radar Target Recognition

Remote Sensing
Micro-Doppler signatures play a crucial role in capturing target features for the radar classification task, and the time–frequency distribution method is widely used to represent micro-Doppler signatures in many applications including human activities ...
Beili Ma, Baixiao Chen
doaj   +1 more source

Orientation-Independent Human Activity Recognition Using Complementary Radio Frequency Sensing

Sensors, 2023
RF sensing offers an unobtrusive, user-friendly, and privacy-preserving method for detecting accidental falls and recognizing human activities. Contemporary RF-based HAR systems generally employ a single monostatic radar to recognize human activities ...
Muhammad Muaaz, Sahil Waqar, Matthias Pätzold   +2 more
doaj   +1 more source

Micro-Doppler Signature Analysis for Space Domain Awareness Using VHF Radar

Remote Sensing
The large quantity of resident space objects orbiting Earth poses a threat to safety and efficient operations in space. Radar sensors are well suited to detecting objects in space including decommissioned satellites and debris, whereas the more commonly ...
Emma Heading, Si Tran Nguyen, David Holdsworth, Iain M. Reid   +3 more
doaj   +1 more source

Time-Frequency Spectral Signature of Limb Movements and Height Estimation Using Micro-Doppler Millimeter-Wave Radar

Sensors, 2020
We present a technique for the identification of human and animal movement and height using a low power millimeter-wave radar. The detection was based on the transmission of a continuous wave and heterodyning the received signal reflected from the target
Yael Balal, Nezah Balal, Yair Richter, Yosef Pinhasi   +3 more
doaj   +1 more source

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

Elastomeric Micro‐Balloons for Remote Control of Cerebral Blood Flow and Real‐Time In vivo Imaging of Rodent Brain Response to Hypoperfusion

Advanced Materials, EarlyView.
This study reports the fabrication of MRI‐compatible elastomeric micro‐balloons via a multi‐step bubble casting process, where the monolithic elastomeric wall is selectively stiffened for reversible and controlled inflation and elasticity, depending on the target vessels for graded occlusion of cerebral arteries.
Jong Bin Kim, Jinghui Wang, Yinding Chi, Jingxian Wu, Alicia Ng, Guanda Qiao, Honglin Tan, Miroslaw Janowski, Piotr Walczak, Yajie Liang, Shu Yang   +10 more
wiley   +1 more source

Enhanced Multi-Channel Feature Synthesis for Hand Gesture Recognition Based on CNN With a Channel and Spatial Attention Mechanism

IEEE Access, 2020
Millimeter-wave (MMW) radar hand gesture recognition technology is becoming important in many electronic device control applications. Currently, most existing approaches utilize the radical and micro-Doppler features from single-channel MMW radar, which ...
Chuan Du, Lei Zhang, Xiping Sun, Junxu Wang, Jialian Sheng   +4 more
doaj   +1 more source