trained model against the training images and show two examples in Fig \[fig:overfitting\_issue\]. The predicted bounding boxes are drawn on the image with confidence scores around each box. Only the boxes with confidence scores higher than 0.05 are displayed. The selected 5 labeled boxes are located at the same position with the predicted boxes and the probability is close to 1. Since the threshold here is 0.05, all the other regions including the unlabeled cars are classified as background with high confidence. This shows that the model overfits the training data severely, which degrades the accuracy.

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   ![Label propagation process on training images of CARPK\_5\_5. The two numbers below the images are the number of expanded boxes and the number of correctly expanded. From the left to the right, the total number of true bounding boxes is 61, 58, 34, respectively. From the top to bottom, the images correspond to the training data for the third, fifth-th, seven-th and the last stage, respectively. The original sampled 5 labeled bounding boxes are shown in blue; the propagated boxes ares shown in yellow; the incorrectly (IoU $<$ 0.3) propagated is shown in red[]{data-label="fig:labelpropagation"}](figs/label_prop_20160524_GF2_00133_10_2.jpg "fig:"){width="\thirdsplitwidth\linewidth"}   ![Label propagation process on training images 