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Radar

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Texture Image Classification Based on Deep Learning and Wireless Sensor Technology.

Computational intelligence and neuroscience
The main purpose of the object detection process is to determine the category of the scene object and use the display 3D and 3D frame size. At present, in the case of 3D object detection, we can extract more accurate features by learning a large numb...

Generation of Human Micro-Doppler Signature Based on Layer-Reduced Deep Convolutional Generative Adversarial Network.

Computational intelligence and neuroscience
Human activity recognition (HAR) using radar micro-Doppler has attracted the attention of researchers in the last decade. Using radar for human activity recognition has been very practical because of its unique advantages. There are several classifie...

Human Being Detection from UWB NLOS Signals: Accuracy and Generality of Advanced Machine Learning Models.

Sensors (Basel, Switzerland)
This paper studies the problem of detecting human beings in non-line-of-sight (NLOS) conditions using an ultra-wideband radar. We perform an extensive measurement campaign in realistic environments, considering different body orientations, the obstac...

Space Target Classification Improvement by Generating Micro-Doppler Signatures Considering Incident Angle.

Sensors (Basel, Switzerland)
Classifying space targets from debris is critical for radar resource management as well as rapid response during the mid-course phase of space target flight. Due to advances in deep learning techniques, various approaches have been studied to classif...

Real-Time Object Detection and Classification by UAV Equipped With SAR.

Sensors (Basel, Switzerland)
The article presents real-time object detection and classification methods by unmanned aerial vehicles (UAVs) equipped with a synthetic aperture radar (SAR). Two algorithms have been extensively tested: classic image analysis and convolutional neural...

Research on the Coordinate Attention Mechanism Fuse in a YOLOv5 Deep Learning Detector for the SAR Ship Detection Task.

Sensors (Basel, Switzerland)
The real-time performance of ship detection is an important index in the marine remote sensing detection task. Due to the computing resources on the satellite being limited by the solar array size and the radiation-resistant electronic components, in...

A novel deep learning method for marine oil spill detection from satellite synthetic aperture radar imagery.

Marine pollution bulletin
Oil spill discharges from operational maritime activities like ships, oil rigs and other structures, leaking pipelines, as well as natural hydrocarbon seepage pose serious threats to marine ecosystems and fisheries. Satellite synthetic aperture radar...

A low-cost approach for soil moisture prediction using multi-sensor data and machine learning algorithm.

The Science of the total environment
A high-resolution soil moisture prediction method has recently gained its importance in various fields such as forestry, agricultural and land management. However, accurate, robust and non- cost prohibitive spatially monitoring of soil moisture is ch...

Pedestrian and Animal Recognition Using Doppler Radar Signature and Deep Learning.

Sensors (Basel, Switzerland)
Pedestrian occurrences in images and videos must be accurately recognized in a number of applications that may improve the quality of human life. Radar can be used to identify pedestrians. When distinct portions of an object move in front of a radar,...

Split BiRNN for real-time activity recognition using radar and deep learning.

Scientific reports
Radar systems can be used to perform human activity recognition in a privacy preserving manner. This can be achieved by using Deep Neural Networks, which are able to effectively process the complex radar data. Often these networks are large and do no...