کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6937738 1449836 2018 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Learning deep similarity models with focus ranking for fabric image retrieval
ترجمه فارسی عنوان
یادگیری مدل های شباهت عمیق با رتبه بندی تمرکز برای بازیابی تصویر پارچه
کلمات کلیدی
00-01، 99-00، شبکه عصبی متقاطع، بازیابی تصویر پارچه تعبیه متریک، رتبه بندی فوکوس
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی
Fabric image retrieval is beneficial to many applications including clothing searching, online shopping and cloth modeling. Learning pairwise image similarity is of great importance to an image retrieval task. With the resurgence of Convolutional Neural Networks (CNNs), recent works have achieved significant progresses via deep representation learning with metric embedding, which drives similar examples close to each other in a feature space, and dissimilar ones apart from each other. In this paper, we propose a novel embedding method termed focus ranking that can be easily unified into a CNN for jointly learning image representations and metrics in the context of fine-grained fabric image retrieval. Focus ranking aims to rank similar examples higher than all dissimilar ones by penalizing ranking disorders via the minimization of the overall cost attributed to similar samples being ranked below dissimilar ones. At the training stage, training samples are organized into focus ranking units for efficient optimization. We build a large-scale fabric image retrieval dataset (FIRD) with about 25,000 images of 4300 fabrics, and test the proposed model on the FIRD dataset. Experimental results show the superiority of the proposed model over existing metric embedding models.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Image and Vision Computing - Volume 70, February 2018, Pages 11-20
نویسندگان
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