کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6941809 870621 2016 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A multi-scene deep learning model for image aesthetic evaluation
ترجمه فارسی عنوان
یک مدل یادگیری عمیق چند مرحله ای برای ارزیابی زیبایی شناسی تصویر
کلمات کلیدی
یادگیری عمیق، زیبایی تصویر، مدل یادگیری عمیق چند مرحله ای، پیش آموزش
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی
Aesthetic evaluation of images has attracted a lot of research interests recently. Previous work focused on extracting handcrafted image features or generic image descriptors to build statistical model for aesthetic evaluation. However, the effectiveness of these approaches is limited by researchers' understanding on the aesthetic rules. In this paper, we present a multi-scene deep learning model (MSDLM) to enable automatic aesthetic feature learning. This deep learning model achieves better results because it improves performance on some major problems, including limited data amount and categories, scenes dependent evaluation, unbalanced dataset, noise data etc. Major innovations are as follows. (1) We design a scene convolutional layer consist of multi-group descriptors in the network elaborately so that the model has a comprehensive learning capacity for image aesthetic. (2) We design a pre-training procedure to initialize our model. Through pre-training the multi-group descriptors discriminatively, our model can extract specific aesthetic features for various scenes, and reduce the impact of noise data when building the model. Experimental results show that our approach significantly outperforms existing methods on two benchmark datasets.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Signal Processing: Image Communication - Volume 47, September 2016, Pages 511-518
نویسندگان
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