کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6940134 1450007 2018 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Boosting image classification through semantic attention filtering strategies
ترجمه فارسی عنوان
افزایش طبقه بندی عکس ها از طریق استراتژی های فیلتر کردن معنایی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی
In this paper, we present three attention filtering strategies based on their saliency map that improve image classification in three different frameworks: Bag of Visual Words, Spatial Pyramid Matching and Convolutional Neural Networks. These approaches remove significant features at the region level that do not belong to the object of interest. We initially propose AutoBlur, a simple but effective approach to automatically select the blurring factor of the Hou's image signature algorithm used in this paper. Then, based on AutoBlur, we introduce two variants of our approach SARF (Semantic Attention Region Filtering), to semantically remove non-relevant regions through a Mean Shift segmentation. The first is based on the intersection of the Hou's image attention areas with its Mean Shift segmentation, while the second one discards regions based on a key point voting system that uses Euclidean distance.120
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition Letters - Volume 112, 1 September 2018, Pages 176-183
نویسندگان
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