Data Labeling and Curation at Scale (DLCS) for Machine Learning Algorithms
ID: DHS241-002Type: Phase I
Overview

Topic

Data Labeling and Curation at Scale (DLCS) for Machine Learning Algorithms

Agency

Department of Homeland SecurityScience and Technology Directorate

Program

Type: SBIRPhase: Phase IYear: 2024

Topic Link

https://www.sbir.gov/node/2477001

Additional Information

https://oip.dhs.gov/sbir/public
Timeline
  1. 1
    Release Nov 8, 2023 12:00 AM
  2. 2
    Open Dec 18, 2023 12:00 AM
  3. 3
    Next Submission Due Jan 18, 2024 12:00 AM
  4. 4
    Close Jan 18, 2024 12:00 AM
Description

The Department of Homeland Security (DHS) is seeking proposals for the topic of "Data Labeling and Curation at Scale (DLCS) for Machine Learning Algorithms" as part of their Small Business Innovation Research (SBIR) program. The DHS Science & Technology Directorate (S&T) generates large volumes of data that are valuable for developing next-generation detection algorithms. Currently, data collection and annotation are time-consuming and labor-intensive processes. DHS is looking for innovative techniques to accelerate and improve data collection, labeling, storing, and distribution processes. The focus should be on novel data ingestion, labeling, and curation techniques, with the ability to process various file formats and generate ground truth data. The solution should also support Government-approved cybersecurity standards. The project duration is not specified, but it is expected to be scalable for long-term use by DHS. The application due date for this Phase I solicitation is January 18, 2024. For more information, visit the SBIR topic link or the solicitation agency URL.

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