کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6940074 869737 2016 34 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Multi-view low-rank dictionary learning for image classification
ترجمه فارسی عنوان
یادگیری فرهنگ لغت چند طبقه ای برای طبقه بندی تصویر
کلمات کلیدی
چندرسانه ای یادگیری فرهنگ لغت، فرهنگ لغت چندرسانه ای کمینه سازی، محدودیت عدم انسجام ساختاری، طبقه بندی نمایندگی همکاری،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی
Recently, a multi-view dictionary learning (DL) technique has received much attention. Although some multi-view DL methods have been presented, they suffer from the problem of performance degeneration when large noise exists in multiple views. In this paper, we propose a novel multi-view DL approach named multi-view low-rank DL (MLDL) for image classification. Specifically, inspired by the low-rank matrix recovery theory, we provide a multi-view dictionary low-rank regularization term to solve the noise problem. We further design a structural incoherence constraint for multi-view DL, such that redundancy among dictionaries of different views can be reduced. In addition, to enhance efficiency of the classification procedure, we design a classification scheme for MLDL, which is based on the idea of collaborative representation based classification. We apply MLDL for face recognition, object classification and digit classification tasks. Experimental results demonstrate the effectiveness and efficiency of the proposed approach.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 50, February 2016, Pages 143-154
نویسندگان
, , , , , ,