کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6939621 | 1449972 | 2018 | 28 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Supervised deep hashing for scalable face image retrieval
ترجمه فارسی عنوان
حشره عمیق را برای بازیابی تصویر چهره مقیاس پذیر تحت نظارت قرار داد
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کلمات کلیدی
بازیابی تصویر، هشیاری تحت نظارت، کدهای دودویی، یادگیری عمیق،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی
Hashing has been widely utilized for Approximate Nearest Neighbor (ANN) search due to its fast retrieval speed and low storage cost. In this work, we propose a novel supervised hashing method for scalable face image retrieval, i.e., Deep Hashing based on Classification and Quantization errors (DHCQ), by simultaneously learning feature representations of images, hash codes and classifiers. The supervised information and the deep architecture are collaboratively explored. Specifically, a deep convolutional network is introduced to learn discriminative feature representations, which are directly used to generate hash codes and predict labels of images. The quantization errors and the prediction errors jointly guide the learning of the deep network. They are highly interrelated and promoted each other. It is worth noting that the proposed method is a general hashing method and can be applied to the general image retrieval task. Extensive experiments on two face image datasets and one general image dataset demonstrate the effectiveness of the proposed method compared with several state-of-the-art hashing methods.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 75, March 2018, Pages 25-32
Journal: Pattern Recognition - Volume 75, March 2018, Pages 25-32
نویسندگان
Jinhui Tang, Zechao Li, Xiang Zhu,