This project will enhance machine understanding of big image and video data sets by including human input as sub-routines inside of larger computational systems. There are many existing marketplaces for micro-work, where people are able to bid and complete small-scale jobs, and humans are much better than machines at resolving issues such as whether a circular object is a face or a wheel. However, building computational systems that contain human feedback is not trivial. This research will focus on characterizing the results of specific human computation platforms and on developing instructions and algorithms that will best incorporate human computation in ways that allow robust computer understanding of large image-based datasets, such as in cancer detection and treatment.
Research partners from MITRE, CITRIS Health, UC Davis and UC Merced worked with health care teams to identify digital health barriers and co-create new ways to address them.
Drought, climate change, an aging infrastructure and growing population threaten the water California’s San Joaquin Valley uses to supply most of the nation’s produce and […]
The UC WATER Security and Sustainability Research Initiative is focused on strategic research to build the knowledge base for better water resources management by applying: […]