You are here

LIFT: Learning Imagery for Few-Shot Training/AriA

Award Information
Agency: Department of Defense
Branch: Office of the Secretary of Defense
Contract: HQ003419P0025
Agency Tracking Number: O182-006-0150
Amount: $224,597.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: SCO182-006
Solicitation Number: 18.2
Timeline
Solicitation Year: 2018
Award Year: 2019
Award Start Date (Proposal Award Date): 2018-12-14
Award End Date (Contract End Date): 2019-06-13
Small Business Information
1222 4th Street SW
Washington, DC 20024
United States
DUNS: 962150483
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Jason E Summers
 Chief Scientist
 (202) 629-9716
 jason.e.summers@ariacoustics.com
Business Contact
 Jason Summers
Phone: (202) 629-9716
Email: jason.e.summers@ariacoustics.com
Research Institution
N/A
Abstract

To support the detection and identification of high-value targets in mission-critical applications, specifically those for which there are few or no sample images, ARiA will develop and demonstrate the feasibility of LIFT (Learning Imagery for Few-Shot Training), a training-data augmentation tool for use in few-shot learning scenarios that: (1) intelligently applies image-processing functions to existing data to generate new training examples, (2) generates realistic synthetic training data given a geometrical model of the target, and (3) learns to select images that help the deep-learning model correctly classify rare targets and generalize to new environments and configurations.The Phase I effort will (1) design and develop a deep reinforcement learning framework that demonstrates a proof-of-concept system capable of improving object detection performance on objects with limited training data and the ability to improve generalizability of object detection to new environments; (2) demonstrate that LIFT can feasibly meet DoD needs through improvements in detection of rare objects within commercial high-resolution satellite imagery as assessed by performance metrics defined in Phase I; and (3) establish that LIFT can be developed into a useful product for DoD that is compatible with existing decision chains and workflows across multiple ISR systems and interfaces.

* Information listed above is at the time of submission. *

US Flag An Official Website of the United States Government