The Department of Defense (DOD) is seeking proposals for the topic of "Image Quality and Task Complexity for Machine Learning" as part of their Small Business Technology Transfer (STTR) Phase I program. The specific agency involved is the National Geospatial-Intelligence Agency. The objective of this solicitation is to explore the relationship between task complexity, image quality, and machine learned model capacity using information theory. The goal is to develop a predictive analytic that can assess machine learning performance for previously unseen image sources. The focus is on down-looking image detection and classification tasks, such as counting civilian vehicles in a factory parking lot. The research will be used for triaging and updating machine learned models' decision confidence based on current image streams. The project duration is divided into two phases: Phase I involves critically assessing the results and identifying suitable operational domains, while Phase II requires justifying the proposal, setting clear milestones, and developing a strong test plan. The ultimate aim is to expand these methods to characterize ML models, other image modalities, and analysis tasks, leading to increased efficiencies in automated image workflow. The solicitation is currently open, with a closing date of June 12, 2024. For more information, interested parties can visit the SBIR topic link at https://www.sbir.gov/node/2606021 or the DOD SBIR/STTR opportunities page at https://www.defensesbirsttr.mil/SBIR-STTR/Opportunities/.