کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
533001 870037 2007 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Hidden annotation for image retrieval with long-term relevance feedback learning
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Hidden annotation for image retrieval with long-term relevance feedback learning
چکیده انگلیسی

Hidden annotation (HA) is an important research issue in content-based image retrieval (CBIR). We propose to incorporate long-term relevance feedback (LRF) with HA to increase both efficiency and retrieval accuracy of CBIR systems. The work contains two parts. (1) Through LRF, a multi-layer semantic representation is built to automatically extract hidden semantic concepts underlying images. HA with these concepts alleviates the burden of manual annotation and avoids the ambiguity problem of keyword-based annotation. (2) For each learned concept, semi-supervised learning is incorporated to automatically select a small number of candidate images for annotators to annotate, which improves efficiency of HA.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 38, Issue 11, November 2005, Pages 2007–2021
نویسندگان
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