Image Quality and Task Complexity for Machine Learning
ID: OSD24B-001Type: BOTH
Overview

Topic

Image Quality and Task Complexity for Machine Learning

Agency

Agency: DODBranch: OSD

Program

Type: STTRPhase: BOTH

Topic Link

https://www.dodsbirsttr.mil/topics-app/

Additional Information

https://www.dodsbirsttr.mil/topics-app/
Timeline
    Description

    The Department of Defense (DOD) is seeking proposals for the Small Business Innovation Research (SBIR) opportunity titled "Image Quality and Task Complexity for Machine Learning." This initiative aims to develop information-theoretic approaches that enhance automation within machine learning workflows, specifically focusing on the relationship between image quality, task complexity, and machine learned model capacity. The work is critical for improving image detection and classification tasks, which are essential for intelligence operations, by generating predictive analytics for machine learning performance from previously unseen image sources. Proposals are due by June 12, 2024, with the opportunity opening on May 15, 2024. Interested parties can find more information and submit proposals through the DOD SBIR/STTR website.

    Files
    Title
    Posted
    1729929015622.pdf
    Similar Opportunities
    Image Labeling for Sparse and Rare Targets in Satellite Imagery for Computer Vision Applications -
    DOD
    The Department of Defense (DoD) is seeking proposals for the Small Business Innovation Research (SBIR) program focused on "Image Labeling for Sparse and Rare Targets in Satellite Imagery for Computer Vision Applications." The objective is to refine existing image labeling methodologies to enhance the production of datasets containing rare and diverse objects of interest (OOIs) in overhead satellite imagery, particularly those that are challenging to identify due to factors such as scarcity, lack of distinctiveness, occlusion, and natural obfuscation. This initiative is critical for improving the efficiency and cost-effectiveness of labeling processes, which are essential for developing machine learning algorithms in computer vision applications. Interested parties must possess TS/SCI clearances and conduct work at the same level, with Phase I proposals due by May 21, 2025, and further details available at the provided source link: https://www.sbir.gov/topics/11947.
    Tools for Test & Evaluation on Incompletely-Labeled Satellite Imagery Datasets -
    DOD
    The Department of Defense (DoD) is seeking proposals for the Small Business Innovation Research (SBIR) program focused on developing tools for test and evaluation of AI/ML models using incompletely-labeled satellite imagery datasets. The objective is to create a software package that can rapidly analyze the performance of various AI/ML models on overhead imagery datasets, particularly in the presence of label noise, which can significantly impact evaluation quality. This initiative is crucial for organizations that rely on large-scale AI/ML deployments, as it aims to enhance confidence in model performance without incurring additional costs or delays. Proposals are due by May 21, 2025, and further details can be found at the provided source link: https://www.sbir.gov/topics/11948.
    Tools for Test & Evaluation on Incompletely-Labeled Satellite Imagery Datasets -
    DOD
    The Department of Defense (DOD) is seeking innovative solutions through the Small Business Innovation Research (SBIR) program for the development of tools aimed at evaluating AI/ML models on incompletely-labeled satellite imagery datasets. The primary objective is to create a flexible system that can reliably estimate the performance of AI/ML models in the presence of label noise, which is a common issue in overhead imagery datasets, thereby enhancing confidence in model performance post-deployment. This opportunity is particularly significant for organizations like the National Geospatial-Intelligence Agency (NGA) that require robust evaluation methods for various computer vision tasks, including object detection and automated target recognition. Interested parties should note that the solicitation is currently in the pre-release phase, with the open date set for April 23, 2025, and a close date of May 21, 2025, by which applications must be submitted. For further details, applicants can visit the DOD SBIR website at https://www.dodsbirsttr.mil/topics-app/.
    Exploring Novel Machine Learning Techniques for Predictive Supply Chain Analytics within DoD and DIB -
    DOD
    The Department of Defense (DoD) is seeking proposals for the Small Business Innovation Research (SBIR) program focused on "Exploring Novel Machine Learning Techniques for Predictive Supply Chain Analytics within DoD and DIB." The objective is to enhance the efficiency and resilience of the Department of the Air Force (DAF) supply chain by developing advanced predictive analytics solutions that leverage machine learning models and existing knowledge graphs. This initiative is crucial for addressing critical supply chain challenges, including demand forecasting, disruption prediction, and resource optimization, ultimately ensuring mission readiness and national security. Interested parties must submit their proposals by May 21, 2025, with further details available at the provided solicitation link.
    Exploring Resilient Supply Chain Autonomous Intelligence Assistant -
    DOD
    The Department of Defense (DoD) is seeking proposals for the Small Business Innovation Research (SBIR) project titled "Exploring Resilient Supply Chain Autonomous Intelligence Assistant," aimed at developing a foundational framework for a Supply Chain Intelligence Platform tailored to the Defense Industrial Base (DIB). The primary objectives include demonstrating the technical feasibility of automated data extraction from open sources and enhanced entity disambiguation within a knowledge graph, which are critical for improving supply chain visibility and decision-making capabilities for the Air Force. This initiative is vital for addressing operational gaps in supply chain management, particularly for platforms like the KC-46, and aims to enhance data integrity and risk analysis through advanced AI-driven analytics. Interested parties must submit their proposals by May 21, 2025, with the project scheduled to commence on April 2, 2025. For more information, please visit the official solicitation page at https://www.sbir.gov/topics/11887.
    Exploring the ability to Enhance Scalability For Knowledge Graphs For Enterprise Solutions -
    DOD
    The Department of Defense (DoD) is seeking proposals for a Phase I Small Business Innovation Research (SBIR) project titled "Exploring the ability to Enhance Scalability For Knowledge Graphs For Enterprise Solutions." The objective of this project is to optimize Knowledge Graph technologies for large-scale predictive analytics within the Defense Industrial Base (DIB), focusing on automating graph construction from diverse data types while ensuring data integrity and security. This initiative is crucial for enhancing the DoD's capabilities in supply chain management and predictive analytics, particularly for applications related to the KC-46 platform and its supply chain. Interested parties must submit their proposals by May 21, 2025, with further details available at the provided source link.
    Capabilities for the Detection or Classification of Physical Damage using Remote Sensing -
    DOD
    The Department of Defense (DOD) is seeking innovative technologies for the automated detection and classification of physical damage using remote sensing, as outlined in the SBIR opportunity titled "Capabilities for the Detection or Classification of Physical Damage using Remote Sensing." The objective is to develop solutions that can automate damage assessments of infrastructure and buildings over large areas, which is crucial for effective resource allocation in humanitarian assistance and disaster recovery efforts. This initiative emphasizes the need for reliable identification of physical damage, with outputs compatible with GIS software and accompanied by confidence values, while ensuring the protection of sensitive algorithm information. Proposals are due by May 21, 2025, with the opportunity accepting both Phase I and Direct to Phase II submissions. Interested parties can find more details and submit proposals through the DOD SBIR website.
    Automated Intelligence Preparation of the Battlespace from Open-Source Information -
    DOD
    The Department of Defense, specifically the Marine Corps, is seeking innovative solutions through the Small Business Innovation Research (SBIR) program to develop automated tools for generating Intelligence Preparation of the Battlespace (IPB) content from open-source information. The objective is to create a system that efficiently analyzes and visualizes mission variables, enabling Marines to leverage AI and machine learning for actionable insights while reducing the time and manpower traditionally required for IPB processes. This initiative is crucial for enhancing operational effectiveness in dynamic tactical situations, with a focus on improving data quality and usability for mission planning. Interested parties should note that the solicitation is set to open on April 23, 2025, with applications due by May 21, 2025, and can find more information at the provided source link.
    AI/ML-Enhanced Risk Management Framework -
    DOD
    The Department of Defense (DoD) is seeking proposals for the development of an AI/ML-Enhanced Risk Management Framework (RMF) software application, aimed at automating the RMF process necessary for achieving Authority To Operate (ATO) for government software and hardware products. The objective is to streamline the current RMF process, which is heavily reliant on manual efforts, by leveraging advanced technologies such as artificial intelligence and machine learning to enhance data-driven decision-making and risk assessment capabilities. This initiative is critical as the DoD faces increasing cyber threats and the need for timely risk management, with a focus on integrating the new platform with existing DoD systems. Proposals are due by May 21, 2025, and interested parties can find more information and submit their applications through the provided links.
    Using AI to Create Multi-Dimensional digital Models from legacy drawings -
    DOD
    The Department of Defense (DoD) is seeking innovative solutions through the Small Business Innovation Research (SBIR) program to develop an AI-driven system for converting 2D engineering drawings into accurate 3D models, aimed at enhancing the sustainment and operational readiness of legacy systems. The project will address critical challenges in maintaining aging equipment by leveraging advanced AI technologies, ultimately supporting the Defense Industrial Base (DIB) and improving mission readiness. This initiative is crucial for revitalizing the DIB, as many legacy platforms rely on outdated schematics that hinder efficient manufacturing and maintenance processes. Interested parties should note that the solicitation is open from April 2, 2025, to May 21, 2025, with further details available at the provided source link.