AIMC Topic: Radar

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Enhanced PRIM recognition using PRI sound and deep learning techniques.

PloS one
Pulse repetition interval modulation (PRIM) is integral to radar identification in modern electronic support measure (ESM) and electronic intelligence (ELINT) systems. Various distortions, including missing pulses, spurious pulses, unintended jitters...

Human Activity Recognition Based on Deep Learning and Micro-Doppler Radar Data.

Sensors (Basel, Switzerland)
Activity recognition is one of the significant technologies accompanying the development of the Internet of Things (IoT). It can help in recording daily life activities or reporting emergencies, thus improving the user's quality of life and safety, a...

Heart Rate Variability Monitoring Based on Doppler Radar Using Deep Learning.

Sensors (Basel, Switzerland)
The potential of microwave Doppler radar in non-contact vital sign detection is significant; however, prevailing radar-based heart rate (HR) and heart rate variability (HRV) monitoring technologies often necessitate data lengths surpassing 10 s, lead...

A benchmarking protocol for SAR colorization: From regression to deep learning approaches.

Neural networks : the official journal of the International Neural Network Society
Synthetic aperture radar (SAR) images are widely used in remote sensing. Interpreting SAR images can be challenging due to their intrinsic speckle noise and grayscale nature. To address this issue, SAR colorization has emerged as a research direction...

Significant wave height prediction from X-band marine radar images using deep learning with 3D convolutions.

PloS one
This research introduces a deep learning method for ocean wave height estimation utilizing a Convolutional Neural Network (CNN) based on the VGGNet. The model is trained on a dataset comprising buoy wave heights and radar images, both critical for ma...

Comparative Analysis of Audio Processing Techniques on Doppler Radar Signature of Human Walking Motion Using CNN Models.

Sensors (Basel, Switzerland)
Artificial intelligence (AI) radar technology offers several advantages over other technologies, including low cost, privacy assurance, high accuracy, and environmental resilience. One challenge faced by AI radar technology is the high cost of equipm...

Developing a deep learning model for sleep stage prediction in obstructive sleep apnea cohort using 60 GHz frequency-modulated continuous-wave radar.

Journal of sleep research
Given the significant impact of sleep on overall health, radar technology offers a promising, non-invasive, and cost-effective avenue for the early detection of sleep disorders, even prior to relying on polysomnography (PSG)-based classification. In ...

Analytical interpretation of the gap of CNN's cognition between SAR and optical target recognition.

Neural networks : the official journal of the International Neural Network Society
Synthetic aperture radar (SAR) automatic target recognition (ATR) is a crucial technique utilized in various scenarios of geoscience and remote sensing. Despite the remarkable success of convolutional neural networks (CNNs) in optical vision tasks, t...

Combined CNN and RNN Neural Networks for GPR Detection of Railway Subgrade Diseases.

Sensors (Basel, Switzerland)
Vehicle-mounted ground-penetrating radar (GPR) has been used to non-destructively inspect and evaluate railway subgrade conditions. However, existing GPR data processing and interpretation methods mostly rely on time-consuming manual interpretation, ...

Challenges in Developing a Real-Time Bee-Counting Radar.

Sensors (Basel, Switzerland)
Detailed within is an attempt to implement a real-time radar signal classification system to monitor and count bee activity at the hive entry. There is interest in keeping records of the productivity of honeybees. Activity at the entrance can be a go...