| 摘要 |
A system and method is provided for automated suspicious object boundary determination using a machine learning system ( 300 ) and genetic algorithms. The machine learning system ( 300 ) is trained ( 204 ) and tested ( 205 ) using sets of pre-categorized examples. Genetic algorithms assign initial parameter values ( 201 ), evaluate the system's performance (206) during testing and assign a performance rating ( 207 ), whereupon if the rating is acceptable, the current machine learning system's settings are assigned as default parameters ( 209 ) for future suspicious object segmentation. However, if the performance rating is unacceptable, the genetic algorithms adjust the settings ( 210 ) and retrain the system using the newly adjusted settings.
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