AIMC Topic: Telemetry

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A Perspective on Passive Human Sensing with Bluetooth.

Sensors (Basel, Switzerland) May 5, 2022
Passive human sensing approaches based on the analysis of the radio signals emitted by the most common wireless communication technologies have been steadily gaining momentum during the last decade. In this context, the Bluetooth technology, despite ...
Artificial Intelligence Wireless Technology Telemetry Humans
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Robust Spatial-Spectral Squeeze-Excitation AdaBound Dense Network (SE-AB-Densenet) for Hyperspectral Image Classification.

Sensors (Basel, Switzerland) Apr 22, 2022
Increasing importance in the field of artificial intelligence has led to huge progress in remote sensing. Deep learning approaches have made tremendous progress in hyperspectral image (HSI) classification. However, the complexity in classifying the H...
Neural Networks, Computer Artificial Intelligence Telemetry
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Robust Ship Detection in Infrared Images through Multiscale Feature Extraction and Lightweight CNN.

Sensors (Basel, Switzerland) Feb 6, 2022
The sophistication of ship detection technology in remote sensing images is insufficient, the detection results differ substantially from the practical requirements, mainly reflected in the inadequate support for the differentiated application of mul...
Ships Telemetry Algorithms Technology Neural Networks, Computer
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Telemetry Data Compression Algorithm Using Balanced Recurrent Neural Network and Deep Learning.

Computational intelligence and neuroscience Jan 10, 2022
Telemetric information is great in size, requiring extra room and transmission time. There is a significant obstruction of storing or sending telemetric information. Lossless data compression (LDC) algorithms have evolved to process telemetric data e...
Data Compression Telemetry Algorithms Deep Learning Neural Networks, Computer
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Deep Transfer Learning for Land Use and Land Cover Classification: A Comparative Study.

Sensors (Basel, Switzerland) Dec 3, 2021
Efficiently implementing remote sensing image classification with high spatial resolution imagery can provide significant value in land use and land cover (LULC) classification. The new advances in remote sensing and deep learning technologies have f...
Neural Networks, Computer Machine Learning Telemetry
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Channel State Estimation in LTE-Based Heterogenous Networks Using Deep Learning.

Sensors (Basel, Switzerland) Nov 19, 2021
Following the continuous development of the information technology, the concept of dense urban networks has evolved as well. The powerful tools, like machine learning, break new ground in smart network and interface design. In this paper the concept ...
Machine Learning Algorithms Telemetry Reproducibility of Results Deep Learning
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A Deep Learning-Based Intrusion Detection System for MQTT Enabled IoT.

Sensors (Basel, Switzerland) Oct 22, 2021
A large number of smart devices in Internet of Things (IoT) environments communicate via different messaging protocols. Message Queuing Telemetry Transport (MQTT) is a widely used publish-subscribe-based protocol for the communication of sensor or ev...
Internet of Things Telemetry Humans Neural Networks, Computer Deep Learning Bayes Theorem
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Artificial intelligence in telemetry: what clinicians should know.

Intensive care medicine Jan 2, 2021
Artificial Intelligence Telemetry Humans
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Application of machine learning to identify predators of stocked fish in Lake Ontario: using acoustic telemetry predation tags to inform management.

Journal of fish biology Nov 3, 2020
Understanding predator-prey interactions and food web dynamics is important for ecosystem-based management in aquatic environments, as they experience increasing rates of human-induced changes, such as the addition and removal of fishes. To quantify ...
Trout Machine Learning Food Chain Animals Salmonidae Ecosystem Acoustics Lakes Ontario Telemetry Fisheries Predatory Behavior Animal Identification Systems
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Continuous Wearable Monitoring Analytics Predict Heart Failure Hospitalization: The LINK-HF Multicenter Study.

Circulation. Heart failure Feb 25, 2020
BACKGROUND: Implantable cardiac sensors have shown promise in reducing rehospitalization for heart failure (HF), but the efficacy of noninvasive approaches has not been determined. The objective of this study was to determine the accuracy of noninvas...
Telemetry Patient Readmission Cloud Computing Risk Assessment Reproducibility of Results Prognosis Diagnosis, Computer-Assisted Aged Equipment Design Female Male Risk Factors Heart Failure Aged, 80 and over Humans Middle Aged Wearable Electronic Devices United States Predictive Value of Tests Machine Learning Time Factors Smartphone
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