Please wait a minute...
Computer & Telecommunication  2018, Vol. 1 Issue (11): 78-80    DOI:
Current Issue | Archive | Adv Search |
Fine Grained Image Localization Based on Bilinear Convolutional Neural Network
First High School of Fu’an City
Download:   PDF(0KB)
Export: BibTeX | EndNote (RIS)      
Abstract  Fine-grained Image recognition is a difficult problem for computer vision area, and it is also a challenge for big data and artificial intelligence. In order to solve this problem, an object localization method based on bilinear convolutional network is proposed. The bilinear convolutional network is used to obtain different features of VGG network, and the intersection set is used as the localization framework. In order to verify the feasibility of this paper, the proposed method is simulated on CUB-200-2011 and Stanford Cars-196. The simulation result shows the accuracy of the proposed method is higher than other representative methods. After adding the Softmax classier, this proposed method improved largely compared with the primitive image as the input.
Key wordsfine-grained recognition      object localization      feature      bilinear network     
Published: 16 January 2019
ZTFLH:  TP393  

Cite this article:

CHEN Si-qi. Fine Grained Image Localization Based on Bilinear Convolutional Neural Network . Computer & Telecommunication, 2018, 1(11): 78-80.

URL:

http://www.computertelecom.com.cn/EN/     OR     http://www.computertelecom.com.cn/EN/Y2018/V1/I11/78

[1] LIU Hui-fang. Research and Application of Anti-fraud Model Based on Big Data of Communication Operator[J]. 电脑与电信, 2021, 1(7): 46-52.
[2] WANG Zhuang-zhuang LI Zhu. Improved Sobel Edge Detection Operator Based on Butterworth Filter[J]. 电脑与电信, 2020, 1(8): 19-22.
[3] HUANG Jing YANG Shu-guo LIU Zi-zheng. AMethod for Image Retrieval with Capsule Network[J]. 电脑与电信, 2020, 1(6): 52-56.
[4] NING Chen ZHANG Li-he WANG Xin . Multi-sensor Image Matching Method Based on Joint Graph Spectral FeatureAnalysis[J]. 电脑与电信, 2020, 1(12): 1-3.
[5] ZHU Yuan-zhi LU Ru-hua LI Jia LI Ya-lan . [J]. 电脑与电信, 2020, 1(10): 9-12.
[6] ZHANG Hui-fang ZONG Cai-le ZHANG Xiao-lin. Chinese Text Feature Classification Based on Distributed Framework[J]. 电脑与电信, 2019, 1(5): 1-7.
[7] TONG Lian. Research and Application of Machine Learning in Big Data[J]. 电脑与电信, 2018, 1(9): 29-31.
[8] . Study on Bidirectional Feature Matching Algorithm Based on Standardized Euclidean Distance[J]. 电脑与电信, 2018, 1(11): 35-40.
[9] Shi Xueying. Study on Feature Representation in Handwritten Numeral Recognition Based on Autoencoders[J]. 电脑与电信, 2017, 1(1-2): 38-39.
[10] Liu Li. Research on the Method of Pronouns Anaphora Resolution Based on Heterogeneous Features Fusion[J]. 电脑与电信, 2016, 1(11): 42-44.
[11] Du Danlei. Comparative Study on School Enterprise Cooperation and Daily Teaching in Computer Science[J]. 电脑与电信, 2015, 1(5): 76-78.
[12] Cui Jian Hou Xiaorong. A Method for Pedestrian Detection Based on Fast Feature Computation[J]. 电脑与电信, 2015, 1(4): 50-65.
[13] Zhang Yixiang, Yang Tiebao. Research on the Failure Detection for DC/DC Converter Based on HMM[J]. 电脑与电信, 2015, 1(1-2): 63-66.
[14] Yan Qiang Zhou Dongmei. The Selection of Basis Functions of Wavelet Transform in Signal Analysis[J]. , 2012, 1(3): 0-0.
[15] Zeng Qingsong. An Action Recognition Method using Sequence Matching-based Embedding[J]. , 2011, 1(03): 0-0.
Copyright © Computer & Telecommunication, All Rights Reserved.
Powered by Beijing Magtech Co. Ltd