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
相关论文
共 50 条
  • [21] Adaptive stochastic resonance based convolutional neural network for image classification
    Duan, Lingling
    Ren, Yuhao
    Duan, Fabing
    CHAOS SOLITONS & FRACTALS, 2022, 162
  • [22] Convolutional neural network based on an extreme learning machine for image classification
    Park, Youngmin
    Yang, Hyun S.
    NEUROCOMPUTING, 2019, 339 : 66 - 76
  • [23] Image-Based Malware Classification Using Convolutional Neural Network
    Kim, Hae-Jung
    ADVANCES IN COMPUTER SCIENCE AND UBIQUITOUS COMPUTING, 2018, 474 : 1352 - 1357
  • [24] Hyperspectral Image Classification Based on Convolutional Neural Network and Dimension Reduction
    Liu, Xuefeng
    Sun, Qiaoqiao
    Liu, Bin
    Huang, Biao
    Fu, Min
    2017 CHINESE AUTOMATION CONGRESS (CAC), 2017, : 1686 - 1690
  • [25] Breast cancer pathological image classification based on a convolutional neural network
    Yu L.
    Xia Y.
    Yan Y.
    Wang P.
    Cao W.
    Harbin Gongcheng Daxue Xuebao/Journal of Harbin Engineering University, 2021, 42 (04): : 567 - 573
  • [26] Image Classification based on Self-attention Convolutional Neural Network
    Cai, Xiaohong
    Li, Ming
    Cao, Hui
    Ma, Jingang
    Wang, Xiaoyan
    Zhuang, Xuqiang
    SIXTH INTERNATIONAL WORKSHOP ON PATTERN RECOGNITION, 2021, 11913
  • [27] A GPU-Based Convolutional Neural Network Approach for Image Classification
    Cengil, Emine
    Cinar, Ahmet
    Guler, Zafer
    2017 INTERNATIONAL ARTIFICIAL INTELLIGENCE AND DATA PROCESSING SYMPOSIUM (IDAP), 2017,
  • [28] Texture based Image Species Classification with Deep Convolutional Neural Network
    Sharma, Geetanjali
    Krishna, C. Rama
    2019 IEEE 5TH INTERNATIONAL CONFERENCE FOR CONVERGENCE IN TECHNOLOGY (I2CT), 2019,
  • [29] Landform Image Classification Based on Sparse Coding and Convolutional Neural Network
    Liu Fang
    Wang Xin
    Lu Lixia
    Huang Guangwei
    Wang Hongjuan
    ACTA OPTICA SINICA, 2019, 39 (04)
  • [30] In Embedded Systems Image Classification with Convolutional Neural Network
    Calik, Rasim Caner
    Demirci, M. Fatih
    2018 26TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU), 2018,