Learning-Based Approach to Estimation of Morphable Model Parameters
dc.date.accessioned | 2004-10-20T21:04:37Z | |
dc.date.accessioned | 2018-11-24T10:23:36Z | |
dc.date.available | 2004-10-20T21:04:37Z | |
dc.date.available | 2018-11-24T10:23:36Z | |
dc.date.issued | 2000-09-01 | en_US |
dc.identifier.uri | http://hdl.handle.net/1721.1/7264 | |
dc.identifier.uri | http://repository.aust.edu.ng/xmlui/handle/1721.1/7264 | |
dc.description.abstract | We describe the key role played by partial evaluation in the Supercomputing Toolkit, a parallel computing system for scientific applications that effectively exploits the vast amount of parallelism exposed by partial evaluation. The Supercomputing Toolkit parallel processor and its associated partial evaluation-based compiler have been used extensively by scientists at MIT, and have made possible recent results in astrophysics showing that the motion of the planets in our solar system is chaotically unstable. | en_US |
dc.format.extent | 1037544 bytes | |
dc.format.extent | 218112 bytes | |
dc.language.iso | en_US | |
dc.title | Learning-Based Approach to Estimation of Morphable Model Parameters | en_US |
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