• 中国精品科技期刊
  • CCF推荐A类中文期刊
  • 计算领域高质量科技期刊T1类
Advanced Search
Zhou Ye, Zhang Junping. Multi-Scale Deep Learning for Product Image Search[J]. Journal of Computer Research and Development, 2017, 54(8): 1824-1832. DOI: 10.7544/issn1000-1239.2017.20170197
Citation: Zhou Ye, Zhang Junping. Multi-Scale Deep Learning for Product Image Search[J]. Journal of Computer Research and Development, 2017, 54(8): 1824-1832. DOI: 10.7544/issn1000-1239.2017.20170197

Multi-Scale Deep Learning for Product Image Search

More Information
  • Published Date: July 31, 2017
  • Product image search is an important application of mobile visual search in e-commerce. The target of product image search is to retrieve the exact product in a query image. The development of product image search not only facilitates people’s shopping, but also results in that e-commerce moves forward to mobile users. As one of the most important performance factors in product image search, image representation suffers from complicated image background, small variance within each product category, and variant scale of the target object. To deal with complicated background and variant object scale, we present a multi-scale deep model for extracting image representation. Meanwhile, we learn image similarity from product category annotations. We also optimize the computation cost by reducing the width and depth of our model to meet the speed requirements of online search services. Experimental results on a million-scale product image dataset shows that our method improves retrieval accuracy while keeps good computation efficiency, comparing with existing methods.
  • Related Articles

    [1]Shi Ruiwen, Li Guanghui, Dai Chenglong, Zhang Feifei. Feature-Oriented and Decoupled Network Structure Based Filter Pruning Method[J]. Journal of Computer Research and Development, 2024, 61(7): 1836-1849. DOI: 10.7544/issn1000-1239.202330085
    [2]Zhang Jing, Wang Ziming, Ren Yonggong. A3C Deep Reinforcement Learning Model Compression and Knowledge Extraction[J]. Journal of Computer Research and Development, 2023, 60(6): 1373-1384. DOI: 10.7544/issn1000-1239.202111186
    [3]Xie Kunpeng, Yi Dezhi, Liu Yiqing, Liu Hang, He Xinyu, Gong Cheng, Lu Ye. SAF-CNN:A Sparse Acceleration Framework of Convolutional Neural Network forEmbedded FPGAs[J]. Journal of Computer Research and Development, 2023, 60(5): 1053-1072. DOI: 10.7544/issn1000-1239.202220735
    [4]Hou Xin, Qu Guoyuan, Wei Dazhou, Zhang Jiacheng. A Lightweight UAV Object Detection Algorithm Based on Iterative Sparse Training[J]. Journal of Computer Research and Development, 2022, 59(4): 882-893. DOI: 10.7544/issn1000-1239.20200986
    [5]Cai Derun, Li Hongyan. A Metric Learning Based Unsupervised Domain Adaptation Method with Its Application on Mortality Prediction[J]. Journal of Computer Research and Development, 2022, 59(3): 674-682. DOI: 10.7544/issn1000-1239.20200693
    [6]Li Minghui, Jiang Peipei, Wang Qian, Shen Chao, Li Qi. Adversarial Attacks and Defenses for Deep Learning Models[J]. Journal of Computer Research and Development, 2021, 58(5): 909-926. DOI: 10.7544/issn1000-1239.2021.20200920
    [7]Wang Ruiqin, Wu Zongda, Jiang Yunliang, Lou Jungang. An Integrated Recommendation Model Based on Two-stage Deep Learning[J]. Journal of Computer Research and Development, 2019, 56(8): 1661-1669. DOI: 10.7544/issn1000-1239.2019.20190178
    [8]Ding Zongyuan, Wang Hongyuan, Chen Fuhua, Ni Tongguang. Person Re-Identification Based on Distance Centralization and Projection Vectors Learning[J]. Journal of Computer Research and Development, 2017, 54(8): 1785-1794. DOI: 10.7544/issn1000-1239.2017.20170014
    [9]Wu Lei, Zhang Wensheng, Wang Jue. Hidden Topic Variable Graphical Model Based on Deep Learning Framework[J]. Journal of Computer Research and Development, 2015, 52(1): 191-199. DOI: 10.7544/issn1000-1239.2015.20131113
    [10]Zhang Huanlong, Hu Shiqiang, Yang Guosheng. Video Object Tracking Based on Appearance Models Learning[J]. Journal of Computer Research and Development, 2015, 52(1): 177-190. DOI: 10.7544/issn1000-1239.2015.20130995

Catalog

    Article views (1980) PDF downloads (1204) Cited by()

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return