Computer Science ›› 2019, Vol. 46 ›› Issue (1): 73-77.doi: 10.11896/j.issn.1002-137X.2019.01.011

• CCDM2018 • Previous Articles     Next Articles

Image Retrieval Algorithm Based on Transfer Learning

LI Xiao-yu1, NIE Xiu-shan1, CUI Chao-ran1, JIAN Mu-wei1, YIN Yi-long2   

  1. (School of Computer Science and Technology,Shandong University of Finance and Economics,Jinan 250014,China)1
    (School of Software,Shandong University,Jinan 250014,China)2
  • Received:2018-05-08 Online:2019-01-15 Published:2019-02-25

Abstract: In recent years,with the development of the Internet and the popularity of smart devices,the number of online store image is explosively growing.At the same time,the number of users who use different types of social networks and media continues to grow.In this case,the multimedia data type that the user uploaded to the network also has changed,the image uploaded by the user contains the visual information that is carried by the image itself,and also contains the label information and text information that the user sets for it.Therefore,how to provide fast and accurate image retrieval results to users is a new challenge in the field of multimedia retrieval.This paper proposed an image retrieval algorithm based on transfer learning.It learns the visual information and the text information at the same time,then migrates the results learnt to the visual information domain,and thus the feature contains cross modal information.Experimental results show that the proposed algorithm can achieve better image retrieval results.

Key words: Cross-modal, Feature extraction, Image retrieval, Transfer learning

CLC Number: 

  • TP391
[1]SCHNEIDER M,SHIHFU C.A Robust Content Based DigitalSignature for Image Authentication[C]//Proceedings,International Conference on Image Processing.1996:227-230.<br /> [2]JIN Y.Image feature extraction algorithm based on PCA/ICA[D].Xi’an:Xi’an University of Electronic Science and Techno-logy,2014.(in Chinese)<br /> 靳洋.基于PCA/ICA的图像特征提取算法研究[D].西安:西安电子科技大学,2014.<br /> [3]WANG E Y.Study on the extraction and recognition of gray image features based on fuzzy clustering[D].Kunming:Yunnan University,2010.(in Chinese)<br /> 王恩永.基于模糊聚类的灰度图像特征提取和识别研究[D].昆明:云南大学,2010.<br /> [4]ZHANG Z L,LI J C,SHEN Z K.On texture feature extraction based on local Walsh transform[J].The signal processing,2005,21(6):589-596.(in Chinese)<br /> 张志龙,李吉成,沈振康.基于局部沃尔什变换的纹理特征提取方法研究[J].信号处理,2005,21(6):589-596.<br /> [5]SATPATHY A,JIANG X,ENG H L.LBP-Based Edge-Texture Features for Object Recognition [J].IEEE Transactions on Ima-ge Processing,2014,23(5):1953-1964.<br /> [6]KIRBY M,SIROVICH L.Application of the Karhunen-Loeve Procedure for the Characterization of Human Faces[J].IEEE Transactions on Pattern Analysis & Machine Intelligence,2002,12(1):103-108.<br /> [7]BELL A J,SEJNOWSKI T J.The independent components of natural scenes are edge filters[J].Vision Research,1997,37(23):3327-3338.<br /> [8]DENG L P.A study of SVM algorithm for face images under multiple algebraic feature extraction methods[J].Information security and Technology,2014,5(10):45-47.(in Chinese)<br /> 邓丽萍.多种代数特征抽取方法下的人脸图像SVM算法研究[J].信息安全与技术,2014,5(10):45-47.<br /> [9]URVOY M,GOUDIA D,AUTRUSSEAU F.Perceptual DFT Watermarking With Improved Detection and Robustness to Geometrical Distortions[J].IEEE Transactions on Information Forensics & Security,2014,9(7):1108-1119.<br /> [10]ZORAN M,ZORAN V.Robustness of SVD Watermarks in Video Sequences Encoded with H.264/AVC[C]//International Scientific Conference on Information,Communication and Energy Systems and Technologies.2014.<br /> [11]HU T S,ZHOU W,JIANG C C.A method of face recognition based on DCT coefficient and Fourier descriptor[J].Journal of Zhejiang University of Technology,2010,38(5):557-560.(in Chinese)<br /> 胡同森,周维,蒋成成.一种基于DCT系数和Fourier描述子的人脸识别方法[J].浙江工业大学学报,2010,38(5):557-560.<br /> [12]LOWE D G.Distinctive Image Features from Scale-Invariant Keypoints[J].International Journal of Computer Vision,2004,60(2):91-110.<br /> [13]BLEI D M,NG A Y,JORDAN M I.Latent dirichlet allocation[J].Journal of Machine Learning Research,2003,3:993-1022.<br /> [14]QUATTONI A,COLLINS M,DARRELL T.Transfer learning for image classification with sparse prototype representations[C]//IEEE Conference on Computer Vision and Pattern Recognition.IEEE,2008:1-8.<br /> [15]PAN S J,YANG Q.A Survey on Transfer Learning[J].IEEE Transactions on Knowledge & Data Engineering,2010,22(10):1345-1359.<br /> [16]OQUAB M,BOTTOU L,LAPTEV I,et al.Learning and Transferring Mid-level Image Representations Using Convolutional Neural Networks[C]//IEEE Conference on Computer Vision and Pattern Recognition.IEEE Computer Society,2014:1717-1724.<br /> [17]TAYLOR M E,STONE P.Transfer Learning for Reinforcement Learning Domains:A Survey[J].Journal of Machine Learning Research,2009,10(10):1633-1685.<br /> [18]DAI W,JIN O,XUE G R,et al.EigenTransfer:a unified framework for transfer learning[C]//International Conference on Machine Learning.ACM,2009:193-200.<br /> [19]ROY S D,MEI T,ZENG W,et al.Social Transfer:cross-domain transfer learning from social streams for media applications[C]//ACM International Conference on Multimedia.ACM,2012:649-658.<br /> [20]TAHMORESNEZHAD J,HASHEMI S.Visual domain adaptation via transfer feature learning[J].Knowledge & Information Systems,2016,50(2):1-21.<br /> [21]NIE W,LIU A,SU Y.Cross-domain semantic transfer from large-scale social media[J].Multimedia Systems,2016,22(1):75-85.<br /> [22]SHAO L,ZHU F,LI X.Transfer Learning for Visual Categorization:A Survey[J].IEEE Transactions on Neural Networks & Learning Systems,2015,26(5):1019-1034.<br /> [23]TAYLOR M E,STONE P.Transfer Learning for Reinforcement Learning Domains:A Survey[J].Journal of Machine Learning Research,2009,10(10):1633-1685.<br /> [24]ZHU F,SHAO L.Weakly-Supervised Cross-Domain Dictionary Learning for Visual Recognition[J].International Journal of Computer Vision,2014,109(1-2):42-59.<br /> [25]LI X,ZHANG L,DU B,et al.Iterative Reweighting Heterogeneous Transfer Learning Framework for Supervised Remote Sensing Image Classification[J].IEEE Journal of Selected To-pics in Applied Earth Observations & Remote Sensing,2017,10(5):2022-2035.<br /> [26]DING Z,FU Y.Robust Transfer Metric Learning for Image Classification[J].IEEE Transactions on Image Processing,2017,PP(99):1.<br /> [27]GHAZI M M,YANIKOGLU B,APTOULA E.Plant identification using deep neural networks via optimization of transfer learning parameters[J].Neurocomputing,2017,235:228-235.<br /> [28]SHI Z,SIVA P,XIANG T.Transfer Learning by Ranking for Weakly Supervised Object Annotation[OL].http://www.bmva.org/bmvc.2012/BMVC/paper078/abstract078.pdf.<br /> [29]RAVISHANKAR H,SUDHAKAR P,VENKATARAMANI R,et al.Understanding the Mechanisms of Deep Transfer Learning for Medical Images[C]//International Workshop on Large-scale Annotation of Biomedical Data & Expert Lablel Synthesis.2016:188-196.
[1] NIE Xiu-shan, PAN Jia-nan, TAN Zhi-fang, LIU Xin-fang, GUO Jie, YIN Yi-long. Overview of Natural Language Video Localization [J]. Computer Science, 2022, 49(9): 111-122.
[2] FANG Yi-qiu, ZHANG Zhen-kun, GE Jun-wei. Cross-domain Recommendation Algorithm Based on Self-attention Mechanism and Transfer Learning [J]. Computer Science, 2022, 49(8): 70-77.
[3] ZHU Cheng-zhang, HUANG Jia-er, XIAO Ya-long, WANG Han, ZOU Bei-ji. Deep Hash Retrieval Algorithm for Medical Images Based on Attention Mechanism [J]. Computer Science, 2022, 49(8): 113-119.
[4] ZHANG Yuan, KANG Le, GONG Zhao-hui, ZHANG Zhi-hong. Related Transaction Behavior Detection in Futures Market Based on Bi-LSTM [J]. Computer Science, 2022, 49(7): 31-39.
[5] ZENG Zhi-xian, CAO Jian-jun, WENG Nian-feng, JIANG Guo-quan, XU Bin. Fine-grained Semantic Association Video-Text Cross-modal Entity Resolution Based on Attention Mechanism [J]. Computer Science, 2022, 49(7): 106-112.
[6] CHENG Cheng, JIANG Ai-lian. Real-time Semantic Segmentation Method Based on Multi-path Feature Extraction [J]. Computer Science, 2022, 49(7): 120-126.
[7] LIU Wei-ye, LU Hui-min, LI Yu-peng, MA Ning. Survey on Finger Vein Recognition Research [J]. Computer Science, 2022, 49(6A): 1-11.
[8] WANG Jun-feng, LIU Fan, YANG Sai, LYU Tan-yue, CHEN Zhi-yu, XU Feng. Dam Crack Detection Based on Multi-source Transfer Learning [J]. Computer Science, 2022, 49(6A): 319-324.
[9] GAO Yuan-hao, LUO Xiao-qing, ZHANG Zhan-cheng. Infrared and Visible Image Fusion Based on Feature Separation [J]. Computer Science, 2022, 49(5): 58-63.
[10] PENG Yun-cong, QIN Xiao-lin, ZHANG Li-ge, GU Yong-xiang. Survey on Few-shot Learning Algorithms for Image Classification [J]. Computer Science, 2022, 49(5): 1-9.
[11] TAN Zhen-qiong, JIANG Wen-Jun, YUM Yen-na-cherry, ZHANG Ji, YUM Peter-tak-shing, LI Xiao-hong. Personalized Learning Task Assignment Based on Bipartite Graph [J]. Computer Science, 2022, 49(4): 269-281.
[12] ZUO Jie-ge, LIU Xiao-ming, CAI Bing. Outdoor Image Weather Recognition Based on Image Blocks and Feature Fusion [J]. Computer Science, 2022, 49(3): 197-203.
[13] ZHANG Shu-meng, YU Zeng, LI Tian-rui. Transferable Emotion Analysis Method for Cross-domain Text [J]. Computer Science, 2022, 49(3): 218-224.
[14] REN Shou-peng, LI Jin, WANG Jing-ru, YUE Kun. Ensemble Regression Decision Trees-based lncRNA-disease Association Prediction [J]. Computer Science, 2022, 49(2): 265-271.
[15] LIU Li-bo, GOU Ting-ting. Cross-modal Retrieval Combining Deep Canonical Correlation Analysis and Adversarial Learning [J]. Computer Science, 2021, 48(9): 200-207.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!