Small sample training method based on target segmentation

A training method and target segmentation technology, applied in the direction of instruments, computing, character and pattern recognition, etc., can solve a large number of training pictures and other problems, and achieve the effect of solving time-consuming and labor-intensive operations

Active Publication Date: 2021-07-16
XIAN MICROELECTRONICS TECH INST +1
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Problems solved by technology

[0004] The purpose of the present invention is to solve the problem of labeling a large number of pixel-level labels in strong supervised semantic segmentation and requiring a large number of training pictures in weak supervised semantic segmentation, and to provide a small sample training method based on target segmentation

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  • Small sample training method based on target segmentation
  • Small sample training method based on target segmentation

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[0032] In order to enable those skilled in the art to better understand the solutions of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only It is an embodiment of a part of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

[0033] It should be noted that the terms "first" and "second" in the description and claims of the present invention and the above drawings are used to distinguish similar objects, but not necessarily used to describe a specific sequence or sequence. It is to be understood that the data so used are interchangeable under appropriate ...

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Abstract

The invention discloses a small sample training method based on target segmentation, and belongs to the field of image semantic segmentation. The method comprises the following steps of: 1, segmenting a target class of a small sample data set to generate an initial pixel-level label; 2, iteratively training a semantic segmentation network on the small sample data set to generate a fine pixel-level label; 3, acting a segmentation result on an original image to obtain a target image; 4, fusing the target image into a large number of images, generating a new image with the target image, and further generating a large number of new images with pixel-level labels; and 5, training the semantic segmentation network by using a large number of new images with pixel-level labels so as to train a reliable semantic segmentation network. According to the method, the time-consuming and labor-consuming operation of manually annotating the pixel-level semantic tag is solved, the refined segmentation of the target can be realized, and good annotation data is provided for image segmentation and target detection.

Description

technical field [0001] The invention belongs to the field of image semantic segmentation, in particular to a small-sample training method based on object segmentation. Background technique [0002] Image semantic segmentation is a task of computer vision. It assigns a semantic label to each pixel, that is, each pixel in the image has a label. The label of is 1, the label of the background is 0. Semantic segmentation is widely used in various fields, including: automatic driving, image diagnosis and other fields. [0003] Image semantic segmentation methods are mainly divided into two categories: strongly supervised semantic segmentation and weakly supervised semantic segmentation. Strongly supervised semantic segmentation requires manual annotation of a large number of pixel-level semantic labels, which is time-consuming and labor-intensive and the quality of the labels varies from person to person; weakly supervised methods do not require pixel-level image labels, but use...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/34G06K9/62
CPCG06V10/267G06F18/214
Inventor 张翔钟升匡乃亮唐磊范建平罗迒哉
Owner XIAN MICROELECTRONICS TECH INST
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