دانلود رایگان مقاله انگلیسی تاثیر گروه لی برای یادگیری عمیق - الزویر 2018

عنوان فارسی
تاثیر گروه لی برای یادگیری عمیق
عنوان انگلیسی
Lie group impression for deep learning
صفحات مقاله فارسی
0
صفحات مقاله انگلیسی
14
سال انتشار
2018
نشریه
الزویر - Elsevier
فرمت مقاله انگلیسی
PDF
کد محصول
E8647
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هوش مصنوعی
مجله
نامه پردازش اطلاعات - Information Processing Letters
دانشگاه
School of Computer Science and Technology - Soochow University - Suzhou - China
کلمات کلیدی
تصور بصری؛ یادگیری عمیق؛ گروه Lie
۰.۰ (بدون امتیاز)
امتیاز دهید
چکیده

Abstract


In this work, we exploit a novel algorithm for capturing the Lie group manifold structure of the visual impression. By developing the single-layer Lie group model, we show how the representation learning algorithm can be stacked to yield a deep architecture. In addition, we design a Lie group based gradient descent algorithm to solve the learning problem of network weights. We show that our proposed technique yields representations that significantly better suited for training deep network and is also computationally efficient.

نتیجه گیری

5. Conclusions


It is easier and faster for computers to recognize target objects by visual impression. This paper learns visual impression with Lie group structure during the training process of neural network by introducing the concept of Stiefel manifold. The constraint of network parameters greatly reduces the value range of parameters space, which is an outstanding advantage compared to the traditional deep learning algorithms. Experiment results further proved that Lie group impression deep learning model is a feasible method. It supplies a new approach to extract features for image recognition by deep learning methods. Based on the research results of this paper, the geometry structure of parameter space needs more in-depth research, which may help to bring a better classification performance.


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