Agile Vision: Adapting Vision Foundation Models in Real-World Contexts. This project aims to develop an adaptive framework for vision foundation models to operate effectively in data-scarce, resource-

Description

Agile Vision: Adapting Vision Foundation Models in Real-World Contexts. This project aims to develop an adaptive framework for vision foundation models to operate effectively in data-scarce, resource-constrained, and evolving environments. It expects to generate new knowledge in adaptive artificial intelligence by integrating data-efficient learning, parameter-efficient fine-tuning, and latency-efficient inference techniques. The expected outcomes include enhanced deployment of vision models in precision agriculture, environmental monitoring, and industrial automation. This will provide substantial benefits, including increased AI efficiency in critical Australian industries, improved decision-making in dynamic environments, and strengthened sovereign AI capabilities aligned with the National AI Strategy. . Scheme: Discovery Early Career Researcher Award. Field: 4605 - Data Management and Data Science. Lead: Dr Yanbin Liu