Titlebook: Mathematical Methods in Image Processing and Inverse Problems; IPIP 2018, Beijing, Xue-Cheng Tai,Suhua Wei,Haiguang Liu Conference proceed

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書(shū)目名稱Mathematical Methods in Image Processing and Inverse Problems影響因子(影響力)




書(shū)目名稱Mathematical Methods in Image Processing and Inverse Problems影響因子(影響力)學(xué)科排名




書(shū)目名稱Mathematical Methods in Image Processing and Inverse Problems網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱Mathematical Methods in Image Processing and Inverse Problems網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱Mathematical Methods in Image Processing and Inverse Problems被引頻次




書(shū)目名稱Mathematical Methods in Image Processing and Inverse Problems被引頻次學(xué)科排名




書(shū)目名稱Mathematical Methods in Image Processing and Inverse Problems年度引用




書(shū)目名稱Mathematical Methods in Image Processing and Inverse Problems年度引用學(xué)科排名




書(shū)目名稱Mathematical Methods in Image Processing and Inverse Problems讀者反饋




書(shū)目名稱Mathematical Methods in Image Processing and Inverse Problems讀者反饋學(xué)科排名

魅力

forebear

Chivalrous

施魔法

易受騙

A New Initialization Method for Neural Networks with Weight Sharing, initialization. In this paper we will propose a new initialization method which will increase training speed and training stability of neural networks with heavy weight sharing. We will also propose a simple yet efficient method to adjust learning rates layer by layer which is indispensable to our initialization.

使迷醉

The Shortest Path AMID 3-D Polyhedral Obstacles,We use the gradient descent method in conjunction with Intermittent Diffusion (ID), a global optimization strategy, to deduce SDEs for the globally optimal solution. Compared to the existing methods, our algorithm is efficient, easier to implement, and able to obtain the solution with any desirable precisions.

Climate

GOUGE

REIGN

A Total Variation Regularization Method for Inverse Source Problem with Uniform Noise,le, the optimization problem is further converted into a minimax problem. Then first order primal-dual method is applied to find the saddle point of the minimax problem. Numerical examples are given to demonstrate that our proposed method outperforms the other testing methods.