Abstract: An embodiment of the invention provides a processing method of a medical image and a computing apparatus for processing a medical image. In the method, one or more image samples are obtained, a tumor region and an appearance feature thereof in the image sample are marked, and an image recognition model is trained according to the image sample, the tumor region thereof, and an appearance feature of a first tumor. The image sample is an image obtained by photographing an animal body. The appearance feature represents an appearance of the first tumor corresponding to the tumor region. The image recognition model identifies a second tumor in an image to be evaluated is a first type. The first type is related to the tumor region and the appearance feature of the first tumor. Accordingly, a prediction accuracy may be improved.

Abstract: The embodiments of the disclosure provide an image pre-processing method for virtual dressing, a virtual dressing system, and a computer-readable storage medium. The method is described below. A cloth image including a cloth and a human body image including a human body are obtained. A human skeleton image corresponding to the human body is generated. A skeleton image area in the human skeleton image is determined based on the cloth image. A specific image area corresponding to the skeleton image area is cropped from the human body image.

Abstract: An embodiment of the invention provides a processing method of a medical image and a computing apparatus for processing a medical image. In the method, one or more image samples are obtained, a tumor region and an appearance feature thereof in the image sample are marked, and an image recognition model is trained according to the image sample, the tumor region thereof, and an appearance feature of a first tumor. The image sample is an image obtained by photographing an animal body. The appearance feature represents an appearance of the first tumor corresponding to the tumor region. The image recognition model identifies a second tumor in an image to be evaluated is a first type. The first type is related to the tumor region and the appearance feature of the first tumor. Accordingly, a prediction accuracy may be improved.

Abstract: A training data increment method, an electronic apparatus and a computer-readable medium are provided. The training data increment method is adapted for the electronic apparatus and includes the following steps. A training data set is obtained, wherein the training data set includes a first image and a second image. An incremental image is generated based on the first image and the second image. A deep learning model is trained based on the incremental image.

Abstract: A training data increment method, an electronic apparatus and a computer-readable medium are provided. The training data increment method is adapted for the electronic apparatus and includes the following steps. A training data set is obtained, wherein the training data set includes a first image and a second image. An incremental image is generated based on the first image and the second image. A deep learning model is trained based on the incremental image.