首页> 外国专利> LEARNING METHOD AND LEARNING DEVICE FOR STRATEGIC TRANSFORMING RGB TRAINING IMAGE SETS INTO NON-RGB TRAINING IMAGE SETS, TO BE USED FOR LEARNING OBJECT DETECTION ON OBJECTS OF IMAGES IN NON-RGB FORMAT, BY USING CYCLE GAN, RESULTING IN SIGNIFICANTLY REDUCING COMPUTATIONAL LOAD AND REUSING DATA

LEARNING METHOD AND LEARNING DEVICE FOR STRATEGIC TRANSFORMING RGB TRAINING IMAGE SETS INTO NON-RGB TRAINING IMAGE SETS, TO BE USED FOR LEARNING OBJECT DETECTION ON OBJECTS OF IMAGES IN NON-RGB FORMAT, BY USING CYCLE GAN, RESULTING IN SIGNIFICANTLY REDUCING COMPUTATIONAL LOAD AND REUSING DATA

机译:通过使用CYCLE GAN,将RGB训练图像集战略性地转换为非RGB训练图像集的学习方法和学习设备,用于对非RGB格式的图像对象进行学习对象检测,从而显著减少计算负载和重用数据

摘要

The present invention provides a learning method and a learning apparatus for converting an RGB training image set into a Non-RGB training image set using a cycle GAN so that it can be used for object detection learning for an object of an image having a Non-RGB format, and It relates to the used test method and test apparatus. More specifically, in the learning method for converting an RGB image tagged with at least one correct answer information to a non-RGB image tagged with at least one correct answer information using a cycle GAN (Cycle Generative Adversarial Network), (a ) when the learning device acquires at least one first image having an RGB format, causes the first transformer to convert the first image into at least one second image having a Non-RGB format, and the first disk By making the reminator check whether the second image is an image having a primary Non-RGB format or an image having a secondary Non-RGB format to generate a (1_1) result, The head Non-RGB format is a Non-RGB format that has not undergone conversion from the RGB format, and the secondary Non-RGB format is a Non-RGB format that has undergone conversion from the RGB format, converting the second image into at least one third image having the RGB format; (b) when the learning device acquires at least one fourth image having the Non-RGB format, the second transformer converts the fourth image into at least one fifth image having the RGB format and the second discriminator generates a (2_1) result by checking whether the fifth image is an image having a primary RGB format or an image having a secondary RGB format, wherein the primary RGB format is It is an RGB format that has not undergone conversion from the Non-RGB format, and the secondary RGB format is an RGB format that has undergone conversion from the Non-RGB format, and causes the first transformer to convert the fifth image to the Non-RGB format. - converting into at least one sixth image having an RGB format; and (c) the learning apparatus, the first image, the second image, the third image, the fourth image, the fifth image, the sixth image, the (1_1) result and the (2_1)th ) calculating one or more losses with reference to at least some of the results, and learning at least a part of parameters of the first transformer, the second transformer, the first discriminator, and the second discriminator; It relates to a learning method and a learning apparatus comprising the, and a test method and a test apparatus using the same.
机译:本发明提供了一种学习方法和学习设备,用于使用循环GAN将RGB训练图像集转换为非RGB训练图像集,以便其可用于具有非RGB格式的图像的对象的对象检测学习,并且本发明涉及所使用的测试方法和测试设备。更具体地说,在用于使用循环GAN(循环生成对抗网络)将标记有至少一个正确答案信息的RGB图像转换为标记有至少一个正确答案信息的非RGB图像的学习方法中,(a)当学习设备获取至少一个具有RGB格式的第一图像时,使第一转换器将第一图像转换为具有非RGB格式的至少一个第二图像,并通过使再混频器检查第二图像是具有主要非RGB格式的图像还是具有次要非RGB格式的图像来生成(1_1)结果,头部非RGB格式是未经RGB格式转换的非RGB格式,次非RGB格式是已经RGB格式转换的非RGB格式,将第二图像转换为至少一个具有RGB格式的第三图像;(b) 当学习设备获取具有非RGB格式的至少一个第四图像时,第二转换器将第四图像转换为具有RGB格式的至少一个第五图像,并且第二鉴别器通过检查第五图像是具有主要RGB格式的图像还是具有次要RGB格式的图像来生成(2_1)结果,其中,主RGB格式为未经非RGB格式转换的RGB格式,次RGB格式为已经非RGB格式转换的RGB格式,并使第一转换器将第五幅图像转换为非RGB格式。-转换成具有RGB格式的至少六分之一图像;以及(c)学习装置、第一图像、第二图像、第三图像、第四图像、第五图像、第六图像、(1_1)结果和(2_1)第二图像,参考至少一些结果计算一个或多个损耗,并学习第一变压器、第二变压器、第一鉴别器和第二鉴别器的至少一部分参数;本发明涉及一种学习方法和学习装置,包括所述学习方法和学习装置,以及使用所述学习方法和学习装置的测试方法和测试装置。

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