ASA(ALT) – Page 14 – Army SBIR|STTR Program

Natural Language Processing

The objective of this topic is to develop Artificial Intelligence / Machine Learning models to augment Natural Language Processing (NLP) capabilities in 2 main challenge areas: relationship detection and aggregation – automatically detecting relationships that exist between the entities that were extracted from the data. Some extracting attributes of entities include: hair color, nationality, model of tank, armor of tank. Pattern recognition, analysis, and exploitation – automatically recognizing patterns such as indications and warnings and courses of actions and analyzing them – is an integral part of this topic.

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Machine Learning (ML) for Breach Routing

This program aims to improve the Explosive Breacher (EB) by closing capability gaps in current breaching techniques left by quickly evolving adversarial technology and aging legacy equipment.

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Graph Neural Networks (GNN) for UxS Collaborative Agent Control

The purpose of this topic is to use recent advancements in Artificial Intelligence, specifically, GNN to be able to collaborate between different AI agents, Unmanned Aerial/Ground Systems (UxS).

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Height of Burst Scoring through Machine Learning

The purpose of this topic is to develop an AI/ML approach to score height of burst automatically, eliminating the man-power required by the current method.

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Asynchronous Neuromorphic Digital Readout Circuit for Infrared Cameras for Autonomous Target Acquisition and Autonomous Vehicles

Most military scenarios consist of highly cluttered and dynamic scenes. Asynchronous on chip smart event cameras can eliminate cluttered scenarios with a much-reduced latency, power, and would be able to hand off images of interest to imbedded autonomous target algorithms.

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Artificial Intelligence/Machine Learning (AI/ML) for Radio Frequency (RF) Modulation Recognition

The purpose of this topic is to demonstrate the ability to interface to a modern Software Defined Radio (SDR) and the Photon digital signal processing framework in order to characterize large swaths of the RF spectrum in near-real-time (NRT) using AI/ML techniques for signal modulation recognition and sorting (Blue Force emitters; Red Force emitters; Civilian emitters);

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Natural Language Processing

Machine Learning (ML) for Breach Routing

Graph Neural Networks (GNN) for UxS Collaborative Agent Control

Height of Burst Scoring through Machine Learning

Asynchronous Neuromorphic Digital Readout Circuit for Infrared Cameras for Autonomous Target Acquisition and Autonomous Vehicles

Artificial Intelligence/Machine Learning (AI/ML) for Radio Frequency (RF) Modulation Recognition

Sensor Synthetic Data Generation

Datalink-Enabled AI for Fires Optimization

Artificial Intelligence-in Automated Scrap Inspection “MVM”

Holistic Wind Correction for Aviation Targeting