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Predicting performance and success of large-scale vision algorithms
Predicting performance and success of large-scale vision algorithms
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机译：预测大型视觉算法的性能和成功
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摘要
Where a plurality of machine learning algorithms is available to process information or data in the furtherance of a task, one of the algorithms may be identified as particularly well-suited or appropriate based on attributes of the information or data. Such attributes of the imaging data may be determined by any means, and a prediction as to the performance (e.g., one or more metrics) or success of each of the algorithms may be made. One of the algorithms may ultimately be selected based on such predictions, as well as the computing resources that are available for executing the algorithms, and any other relevant constraints.
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