Military AI
 
 
APRIL 2020

Military AI brought to you by the editors of Mil-Embedded.com focuses on artificial intelligence technology in the defense and aerospace domain, bringing readers coverage on machine learning, neural networks, and deep learning techniques leveraged in military and aerospace applications.
 
 
 
 
 
 
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EMMA HELFRICH, ASSOCIATE EDITOR
 
Iris Automation announced the launch of Casia 360 – an onboard detect-and-avoid (DAA) solution with a 360-degree radial field of view to enable commercial Beyond Visual Line of Sight (BVLOS) operations for Unmanned Aircraft Systems (UAS).
 
 
 
 
 
 
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EMMA HELFRICH, ASSOCIATE EDITOR
 
Fortem Technologies, Inc., counter-drone security and defense solutions company, announced the shipment of the new AI-enabled F700 DroneHunter. Designed to combat ineffective ground station jamming, the F700 is intended to be a deterrent against the rising number of adversarial unmanned aerial vehicles (UAV).
 
 
 
 
 
 
 
 
Abaco Systems
 
 
 
 
 
 
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EMMA HELFRICH, ASSOCIATE EDITOR
 
SteelCloud LLC announced that its ConfigOS STIG compliance software has been selected to automate STIG compliance for a Department of Defense Unmanned Aerial Vehicle (UAV) program.
 
 
 
 
 
 
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EMMA HELFRICH, ASSOCIATE EDITOR
 
Mitcham Industries, Inc. announced that its Klein Marine Systems unit has recently delivered the first micro-MA-X (µMA-X System) in support of U.S. Navy Next Generation Small-Class Unmanned Undersea Vehicle (UUV) evaluation sponsored by the Defense Innovation Unit (DIU).
 
 
 
 
 
 
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EMMA HELFRICH, ASSOCIATE EDITOR
 
Raytheon Company and Uptake, industrial-use artificial intelligence (AI) software company, have teamed to bring predictive maintenance capabilities to deployed U.S. Marine Corps teams using M88 armored recovery vehicles.
 
 
 
 
 
 
 
 
 
 
 
Increasingly, end users of embedded and IoT devices expect snappy, intuitive, and interactive graphical user interfaces on IoT endpoints.
 
 
 
 
 
 
 
 
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LISA DAIGLE, ASSISTANT MANAGING EDITOR
 
FLIR Systems has launched the Ranger HDC MR, a new high-definition midrange high-definition thermal-imaging surveillance system that uses embedded analytics and image-processing algorithms to reduce the cognitive workload, enabling operators to distinguish quickly between true threats and false alarms, even in degraded weather conditions.
 
 
 
 
 
 
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EMMA HELFRICH, ASSOCIATE EDITOR
 
After testing, evaluation, and operational assessments from over two dozen customer groups, Citadel Defense has received $9.2 million in orders for their counter-unmanned aerial system (C-UAS) capabilities in the first two months of the year. According to the company, Citadel's Titan C-UAS technology will be used to protect high-value assets in urban, rural, and maritime environments.
 
 
 
 
 
 
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LISA DAIGLE, ASSISTANT MANAGING EDITOR
 
The U.S. military is developing new types of facial-recognition technologies – systems vitally important for the safety of soldiers in the field – to train artificial intelligence (AI) systems to perform identity verification and threat detection, but these advances can also come with some cybersecurity issues.
 
 
 
 
 
 
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TAMMY CARTER CURTISS-WRIGHT DEFENSE SOLUTIONS
 
In this latest column for our ongoing series on Deep Learning, we will consider the question, “How can I teach my machine to learn?” Like humans, machines learn from experience. They make observations from inputs of images, text, or other data, and then look for patterns. After the machine runs through the mathematical layers, it learns to make better decisions based on the examples it was given.
 
 
 
 
 
 
 
 
Sponsored by: Abaco Systems, Annapolis Micro Systems, Pentek
Date: April 29, 2:00 p.m. ET
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