An Image Classification Algorithm of Financial Instruments Based on Convolutional Neural Network

被引:3
|
作者
Dong, Jingfei [1 ]
Li, Xun [2 ]
机构
[1] Sichuan Univ, Business Sch, Chengdu 610005, Peoples R China
[2] Sichuan Int Studies Univ, Res Ctr Int Business & Econ, Chongqing 400030, Peoples R China
关键词
financial instruments; convolutional neural network (CNN); image classification; momentum weight update; weight attenuation;
D O I
10.18280/ts.370618
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The boom of global economy has caused an explosive growth in the issuance and use of financial instruments. Traditionally, the financial instruments are recognized and classified manually, which increases the burden of financial staff and consumes lots of financial time. To solve the problems, this paper designs a convolutional neural network (CNN) for classification of financial instruments, covering components like traditional CNN, shallow convolutional layers, and cropping structure. Then, the momentum weight update was combined with weight attenuation to accelerate the model learning. In addition, the authors designed a preprocessing method for rapid pixel-level adjustment of financial instruments, enabling the proposed CNN to classify financial instruments of various sizes. Experiments show that our CNN can identify various financial instruments, and classify them at an accuracy as high as 96%.
引用
收藏
页码:1055 / 1060
页数:6
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