کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
484854 703295 2015 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Regularized Extreme Learning Machine for Large-scale Media Content Analysis
ترجمه فارسی عنوان
ماشین مجازی افراطی برای تحلیل محتوای رسانه ای در مقیاس بزرگ؟
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر علوم کامپیوتر (عمومی)
چکیده انگلیسی

In this paper, we propose a new regularization approach for Extreme Learning Machine-based Single- hidden Layer Feedforward Neural network training. We show that the proposed regularizer is able to weight the dimensions of the ELM space according to the importance of the network's hidden layer weights, without imposing additional computational and memory costs in the network learning process. This enhances the network's performance and makes the proposed approach suitable for learning non- linear decision surfaces in large-scale classification problems. We test our approach in medium- and large-scale face recognition problems, where we observe its superiority when compared to the existing regularized Extreme Learning Machine classifier in both constrained and unconstrained problems, thus making our approach applicable in demanding media analysis applications such as those appearing in digital cinema production.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Procedia Computer Science - Volume 53, 2015, Pages 420-427