Allows small businesses to submit to Direct to Phase II applications if they performed the Phase I research through other funding sources.
The purpose of this topic is to establish a comprehensive RF-based database that will be used to train a deep learning computer vision algorithm for a target detection system.
Synthetic RF Training Data Generation Read More »
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.
Natural Language Processing Read More »
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.
Height of Burst Scoring through Machine Learning Read More »
US Army requires large-scale, accurate and easily accessible training, test, and validation data to support AI model development for multiple security domains (e.g. SIPR, JWICS…).
Sensor Synthetic Data Generation Read More »
It is projected in the future fight, the speed of battle will be imperative and every munition employed must be effective.
Datalink-Enabled AI for Fires Optimization Read More »
Develop/demonstrate the capability to measure multi-directional winds from the aviation platform to the target, and accommodating platform motion in real time.
Holistic Wind Correction for Aviation Targeting Read More »
