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METHOD FOR ASSESSING AESTHETIC QUALITY OF NATURAL IMAGE BASED ON MULTI-TASK DEEP LEARNING

机译:基于多任务深度学习的自然图像美学质量评估方法

摘要

The present application discloses a method for assessing aesthetic quality of a natural image based on multi-task deep learning. Said method includes: step 1: automatically learning aesthetic and semantic characteristics of the natural image based on multi-task deep learning; step 2: performing aesthetic categorization and semantic recognition to the results of automatic learning based on multi-task deep learning, thereby realizing assessment of aesthetic quality of the natural image. The present application uses semantic information to assist learning of expressions of aesthetic characteristics so as to assess aesthetic quality more effectively, besides, the present application designs various multi-task deep learning network structures so as to effectively use the aesthetic and semantic information for obtaining highly accurate image aesthetic categorization. The present application can be applied to many fields relating to image aesthetic quality assessment, including image retrieval, photography and album management, etc.
机译:本申请公开了一种基于多任务深度学习评估自然图像的美学质量的方法。所述方法包括:步骤1:基于多任务深度学习,自动学习自然图像的美学和语义特征;步骤2:基于多任务深度学习对自动学习的结果进行美学分类和语义识别,从而实现对自然图像美学质量的评估。本申请使用语义信息来辅助学习美学特征的表达,从而更有效地评估美学质量,此外,本申请设计了各种多任务深度学习网络结构,以便有效地利用美学和语义信息来获得较高的美学价值。准确的图像美学分类。本申请可以应用于与图像美学质量评估有关的许多领域,包括图像检索,摄影和相册管理等。

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