Mosaic ATM received a NASA award to use deep learning to predict the low-altitude signal strength of an Advanced Air Mobility vehicle.
Mosaic ATM recently announced a collaboration with GE Aviation and SmartSky Networks to enhance Flight Management Systems (FMS) and Air Traffic Management (ATM) for Advanced Air Mobility (AAM). The combined work effort, conducted under a NASA Innovation Award, uniquely connects the airborne and cloud-based FMS to optimize airspace management while Read more…
We decided to approach this problem as a similarity learning modeling effort. We used convolutional neural networks to train a model that takes an image or video as input and outputs a vector representation of the input, such that similar inputs will be close to each other in the vector space. The vector learning is driven by a triplet loss function.
Designing and deploying machine vision is a powerful technology that humans can employ to improve their decision making. These deep learning and AI techniques are not easily developed, and trained data scientists need to be involved in the translation of analytics to business insights.
Computer vision is a powerful AI technique with vast business applications. In this white paper, Mosaic examines how to use machine vision for detecting airport layouts from the sky.