SBIR/STTR Research Award

TALON: Multi-INT Metadata Extraction for Threat Detection

Award identifier b1f40da336159e93ed3250d1fa474006552e793bba59f3f624c5b0e9ff45580fAwarding agency Department of Defense · Navy

Award amount

$991,701

Program and phase

SBIR · Phase II

Award year

2024

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Award details

Awarding agency
Department of Defense
Branch
Navy
Recipient company
VISION SYSTEMS INC
Proposal award date
2024-03-18
Contract end date
2026-03-31
UEI
NYNGSYWCWNJ5
Solicitation number
22.2
Topic code
N222-118

Research abstract

Identifying and tracking developing threats across a large and growing set of data sources remains a critical unsolved problem. Currently, multi-modal data (images, video, audio clips, satellite images, etc.) as well as OSINT data (social media platforms like Twitter, Telegram, etc.) must be manually inspected by an analyst to extract relevant metadata, such as ōwhoö, ōwhatö, ōwhereö, ōwhenö, and ōwhyö. Subsequent correlation across multiple modalities, required to identify and track developing threats in operational domains, is also a manual process. Recent advances in computer vision, machine learning (ML), and natural language processing (NLP) technology have resulted in the creation of innovative algorithms capable of assisting an analyst in understanding, cataloging, and characterizing multi-modal content automatically. However, these advances have seen limited application to defense and intelligence problems. Vision Systems Inc. (VSI) with support from STR proposes TALON, an innovative multi-INT analysis framework designed to generate information-rich metadata across multi-INT data streams and use the context provided by this metadata to detect emerging threats. In Phase I, TALON leveraged advances in ML and NLP to discover events from publicly available social media and online sources and produce flexible and semantically rich natural-language descriptions of associated multi-modal data. The proposed SBIR Phase II program will build on Phase I results, enhancing and expanding metadata generation capabilities, analyzing metadata using the latest in state-of-the-art NLP systems such as Large Language Models (LLMs) models, and considering operational data sources of interest to potential stakeholders across the defense and intelligence community. The VSI and STR team is uniquely suited to this project, offering unparalleled expertise in machine learning, natural language processing, and remote sensing; extensive experience in the development of innovative software solutions for challenging defense and intelligence problems; and a thorough understanding of the needs of image analysts across the defense and intelligence community.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

25 SBIR/STTR records share this UEI (2012–2026). Reported award amounts total $14,520,455. Reported amounts are not federal obligations.

Phases: Phase I, Phase II, Phase II – Direct to Phase II

Agencies: Department of Defense

Agency intelligence

Department of Defense

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