| 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. |
