کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6863690 | 1439518 | 2018 | 32 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Multi-modal self-paced learning for image classification
ترجمه فارسی عنوان
یادگیری گام های چندگانه برای طبقه بندی تصویر
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کلمات کلیدی
طبقه بندی عکس، یادگیری برنامه درسی، یادگیری خود بخشی، چند منظوره
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
Self-paced learning (SPL) is a powerful framework, where samples from easy ones to more complex ones are gradually involved in the learning process. Its superiority is significant when dealing with challenging vision tasks, like natural image classification. However, SPL based image classification can not deal with information from multiple modalities. As images are usually characterized by visual feature descriptors from multiple modalities, only exploiting one of them may lose some complementary information from other modalities. To overcome the above problem, we propose a multi-modal self-paced learning (MSPL) framework for image classification which jointly trains SPL and multi-modal learning into one framework. Specifically, the multi-modal learning process with curriculum information and the curriculum learning process with multi-modal information are iteratively performed until the final mature multi-modal curriculum is learned. As this multi-modal curriculum can grasp the easy to hard knowledge from both the sample level and the modality level, a better model can be learned. Experimental results on four real-world datasets demonstrate the effectiveness of the proposed approach.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 309, 2 October 2018, Pages 134-144
Journal: Neurocomputing - Volume 309, 2 October 2018, Pages 134-144
نویسندگان
Wei Xu, Wei Liu, Xiaolin Huang, Jie Yang, Song Qiu,