Advanced Artificial Intelligence/Machine Learning Techniques for Automated Target Recognition (ATR) Using Small/Reduced Data Sets
ID: N241-025Type: BOTH
Overview

Topic

Advanced Artificial Intelligence/Machine Learning Techniques for Automated Target Recognition (ATR) Using Small/Reduced Data Sets

Agency

Department of DefenseN/A

Program

Type: SBIRPhase: BOTHYear: 2024

Topic Link

https://www.sbir.gov/node/2479725

Additional Information

https://www.defensesbirsttr.mil/SBIR-STTR/Opportunities/
Timeline
  1. 1
    Release Nov 29, 2023 12:00 AM
  2. 2
    Open Jan 3, 2024 12:00 AM
  3. 3
    Next Submission Due Feb 21, 2024 12:00 AM
  4. 4
    Close Feb 21, 2024 12:00 AM
Description

The Department of Defense (DOD) is seeking proposals for their SBIR 24.1 BAA solicitation. The specific topic of the solicitation is "Advanced Artificial Intelligence/Machine Learning Techniques for Automated Target Recognition (ATR) Using Small/Reduced Data Sets". The Navy branch is responsible for this topic.

The objective of this solicitation is to develop an innovative automatic target recognition (ATR) capability that utilizes state-of-the-art Artificial Intelligence/Machine Learning (AI/ML) technology to support naval mine countermeasure (MCM) operations using reduced data sets. ATR is the ability for a system or algorithm to recognize and identify targets based on data obtained from sensors. In Navy MCM operations, sensors collect data to identify and localize targets of interest in marine environments.

The Navy is interested in developing AI/ML ATR processing algorithms or techniques that can facilitate target detection and identification using smaller data sets to train the algorithms and perform ATR. The current ATR algorithms require large amounts of data to train, which is costly and time-consuming to obtain. The proposed solution should demonstrate a reduction in the amount of data required to train algorithms by an order-of-magnitude smaller without degradation to identification performance and no increase in the probability of false alarms. Advanced ML techniques such as One Shot, Multi Shot, Few Shot, etc. are encouraged.

The ATR capability will be initially integrated into the Navy's Generalized ATR (GATR) framework to improve detection and classification performance. The capability could eventually be integrated into a towed body to support in-stride ATR.

The project will be conducted in two phases. Phase I involves developing a concept to facilitate target identification using smaller data sets and demonstrating its feasibility through testing and analytical modeling. Phase II focuses on developing and delivering a prototype for evaluation, validating its performance against government-provided target truth, and preparing a Phase III development plan for technology transition.

The technology developed under this effort has potential applications in subsea platform autonomy, such as subsea oil and gas pipeline inspection.

The solicitation is closed, and more information can be found on the Defense SBIR/STTR website.

Files
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