Title:

HASTE: Hierarchical Analysis of Spatial and Temporal Data From intelligent data acquisition via smart data-management to confident prediction

Speaker:

Carolina Wählby, Division of Visual Information and Interaction, Dept. of IT, UU

Andreas Hellander, Division of Scientific Computing, Dept. of IT, UU

Abstract:

Images contain very rich information, and digital cameras combined with image processing and analysis can detect and quantify a range of patterns and processes. The valuable information is however often sparse, and the ever increasing speed at which data is collected results in data-volumes that exceed the computational resources available.

The HASTE project takes a hierarchical approach to acquisition, analysis, and interpretation of image data. We develop computationally efficient measurements for data description, confidence-driven machine learning for determination of interestingness, and a theory and framework to apply intelligent spatial and temporal information hierarchies, distributing data to computational resources and storage options based on low-level image features.