Sentence examples similar to monitoring machine learning from inspiring English sources

The BAE systems established a project for fleet health monitoring and machine learning technology for CBM and applied this system to heavy duty transit bus to enable fleet health management remotely in different cities [29].

We also go over various applications that are enabled by cost-effective and compact implementations of lensless microscopy, including some recent work on air quality monitoring, which utilized machine learning for high-throughput and accurate quantification of particulate matter in air.

By combining an array of sensors around the car and using machine learning computers to monitor the data, the car will prevent you from having an accident.

In this paper machine learning algorithm using vibration monitoring is proposed as a possible solution to this problem.

Vibration based machine learning approach for condition monitoring of hydraulic brake system is gaining momentum.

JASK is emerging from stealth today with $12 million in the bank and a machine learning technology that automates network monitoring and management for overtaxed security teams.

We illustrate the performance of this wireless sensor platform on complex problems arising in smart cities, such as traffic flow monitoring, machine-learning-based flash flood monitoring or Kalman-filter based vehicle trajectory estimation.

Apply Machine Learning (ML) to continuous noninvasive vital sign (VS) monitoring data of patients experiencing CRImild, and predict which of these patients will deteriorate to CRIcrit.

Recently, Micropilot, a software tool that monitors image data acquisition from commercial-microscope platforms and identifies events or phenotypes using machine learning techniques has been described 32.

Machine learning engineering happens in three stages — data processing, model building and deployment and monitoring.

Rather than gathering information on attacks and monitoring hacking teams, Darktrace focuses on monitoring a company's own network and detecting low-level anomalies that might indicate an attack — using machine learning technology to do so.