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王權富貴:RCNN的成長曆程

  • 暴力目標檢測                                                                                                 

    •  滑動視窗(從左到右,從上到下)(多個尺寸大小)                               

 

  •   輸入圖片歸一化                                                                                                                      

 

 

 

  • R-CNN                                                                                                            

    •  選擇性搜尋                                                                                            

 

  •  ROI圖片歸一化                                                                                     
  •  使用選擇搜尋有風險,合併太大,會損失目標(損失的是重疊目標)。合併太小,資料太多                                                                     

總:

 

 

 

 

 

  • Fast R-CNN                                                                                                     

  •  邊界框迴歸器                                                                                         

 

  •  在卷積特徵提取後使用Selectiv Search搜尋方法                                     

 

  •  特徵圖塊歸一化(ROI池化)                                                                

 

 

  •  Faster R-CNN                                                                 

  •  候選區域網路(RPN)                                                                           

 

 

 

 

  • YOLO                                       

    •  訓練迴歸框                      
    •  暴力設S*S的網路           
      •  太大不精確               
      •  太小分類不好做        

 

 

 

  •  SSD                                                          

  •  多尺度檢測                             

 

  •  卷積測物,加框先驗