Design of adaptive spatiotemporal information and control systems

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Steep increases in the data gathering, processing and networking capabilities of today's remote sensing systems have put remote sensing firmly on the path to become a pervasive technology, affecting society in a variety of ways. What is now critically needed are powerful object detection and scene interpretation methods amenable to automated processing and interpretation of this wealth of information. This project builds on the synergy of learning control and pattern recognition/image processing to propose innovative techniques for modeling, monitoring, and control of complex, dynamic spatiotemporal systems as encountered mainly in environmental applications. The overall objective is to develop an integrated design methodology that addresses issues relating to the adaptive processing of large quantities of multi-dimensional, heterogeneous sensor data. More specific objectives include research on theoretical and methodological foundations for the design and optimization of biologically-inspired attentive vision algorithms for spatiotemporal saliency in heterogeneous, sparse remote sensing imagery, and the development of novel iterative learning methods to solve ill-posed object detection and classification problems. The methodological approach has been defined in the context of the scarcity of ground truth reference information, which can be difficult and costly to acquire. It involves the development of hybrid technologies integrating kernel-based methods and pertinent machine learning paradigms (deterministic learning and iterative learning) for time-variable, uncertain system monitoring and control applications. This interdisciplinary project will help develop research personnel at all levels, with its training program significantly enhanced by the opportunities arising from the collaboration with industrial partners. Apart from the contribution to new scientific knowledge, the results of this research will directly benefit Canadian society, helping to meet the need for sophisticated information technologies to efficiently monitor and manage natural resources in Canada's vast territory.