Robust Computer Vision for Better Object Detection with Limited Training Data
ID: A244-033Type: BOTH
Overview

Topic

Robust Computer Vision for Better Object Detection with Limited Training Data

Agency

Department of DefenseN/A

Program

Type: SBIRPhase: BOTHYear: 2024

Topic Link

https://www.sbir.gov/node/2651291

Additional Information

https://www.defensesbirsttr.mil/SBIR-STTR/Opportunities/
Timeline
    Description

    The Department of Defense (DOD) is seeking proposals for the topic "Robust Computer Vision for Better Object Detection with Limited Training Data" as part of their SBIR 24.4 Annual solicitation. The goal of this topic is to experiment with innovative AI/ML approaches to object identification and imagery scene analysis. The increasing availability of digital imagery requires automated methods to process and analyze vast amounts of multi-modal data efficiently. One critical application is the identification of objects of interest (OoI) within imagery data or the scene generated by the imagery, which can provide valuable insights and facilitate decision-making processes in various fields such as military intelligence, environmental monitoring, transportation management, and security surveillance.

    The solicitation is open for Direct to Phase II (DP2) proposals with a cost of up to $2,000,000 for an 18-month period of performance. Proposers interested in submitting a DP2 proposal must provide documentation to substantiate that the scientific and technical merit and feasibility equivalent to a Phase I project has been met. The focus of this SBIR topic is robust AI/ML object detection techniques for computer vision that do not rely on extensive availability of labeled training data. The use of foundational knowledge and methods, such as handcrafted features, evolutionary algorithms, and newer techniques based on transformers, can be leveraged for this topic without requiring a feasibility study.

    During DP2, firms should develop and implement novel or hybrid AI/ML models for object detection that do not rely on extensive training data and train models in Project Linchpin's AI Unclassified Operations Environment using Linchpin data for DOD use cases. The Phase III dual-use applications include autonomy, retail, public safety, traffic management, enhanced security, and agriculture. Computer vision solutions in the private sector encompass a wide range of applications, and companies like Amazon, Google, and Microsoft offer cloud-based object detection and recognition services.

    The solicitation is open until March 31, 2025. For more information and to submit a proposal, visit the DOD SBIR website: link.

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