Acer Inc.

Shang-Lin Chung

Chien-Hung Li

The disclosure provides an image segmentation model training method and an electronic device. The method includes the following steps. A plurality of labeled images of a training image are obtained, wherein each of the labeled images includes a labeled target area and a background area. A union area of the labeled target areas of the plurality of labeled images is obtained, and a complement area of the union area is obtained. A predicted segmented image of the training image is generated using an image segmentation model. A first loss value is generated according to the predicted segmented image and the complement area. A second loss value is generated according to the predicted segmented image and the labeled target area of at least one of the plurality of labeled images. The image segmentation model is trained according to the first loss value and the second loss value.

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New Taipei, Taiwan

Shang-Lin Chung