Details of Research Outputs

TitleFF-CMnet: A CNN-Based Model for Fine-Grained Classification of Car Models Based on Feature Fusion
Author (Name in English or Pinyin)
Yu, Y.1,2; Jin, Q.1; Wen Chen, C.2
Date Issued2018-10-08
Source PublicationProceedings - IEEE International Conference on Multimedia and Expo
ISSN19457871
DOI10.1109/ICME.2018.8486443
Indexed BySCOPUS
Firstlevel Discipline计算机科学技术
Education discipline科技类
Published range国外学术期刊
Volume Issue Pages卷: 2018-July
References
[1] B. L. Zhang, "Reliable Classification of Vehicle Types Based on Cascade Classifier Ensembles", IEEE Transactions on Intelligent Transportation Systems, vol. 14, no. 1, pp. 322-332, 2013.
[2] J. W. Hsieh, L. C. Chen, and D. Y. Chen, "Symmetrical SURF and Its Applications to Vehicle Detection and Vehicle Make and Model Recognition", IEEE Transactions on Intelligent Transportation Systems, vol. 15, no. 1, pp. 6-20, 2014.
[3] Y. L. Lin, V. I. Morariu, W. Hsu, and L. S. Davis, "Jointly Optimizing 3D Model Fitting and Fine-Grained Classification", Computer Vision-Eccv 2014, Pt Iv, vol. 8692, pp. 466-480, 2014.
[4] J. Krause, M. Stark, J. Deng, and F. F. Li, "3D Object Representations for Fine-Grained Categorization", 2013 IEEE International Conference on Computer Vision Workshops (Iccvw), pp. 554-561, 2013.
[5] J. Sochor, A. Herout, and J. Havel, "BoxCars: 3D Boxes as CNN Input for Improved Fine-Grained Vehicle Recognition", 2016 IEEE Conference on Computer Vision and Pattern Recognition (Cpvr), pp. 3006-3015, 2016.
[6] L. J. Yang, P. Luo, C. C. Loy, and X. Tang, "A Large-Scale Car Dataset for Fine-Grained Categorization and Verification", 2015 IEEE Conference on Computer Vision and Pattern Recognition (Cvpr), pp. 3973-3981, 2015.
[7] A. Krizhevsky, I. Sutskever, and G. E. Hinton, "ImageNet Classification with Deep Convolutional Neural Networks", Communications of the Acm, vol. 60, no. 6, pp. 84-90, 2017.
[8] P. Sermanet, D. Eigen, X. Zhang, M. Mathieu, R. Fergus, and Y. LeCun, "Overfeat: Integrated recognition, localization and detection using convolutional networks. " Eprint Arxiv, 2013.
[9] C. Szegedy et al., "Going Deeper with Convolutions", 2015 IEEE Conference on Computer Vision and Pattern Recognition (Cvpr), pp. 1-9, 2015.
[10] Y. Bai, F. Gao, et al. "Incorporating Intra-Class Variance to Fine-Grained Visual Recognition. " In Multimedia and Expo (ICME), 2017 IEEE International Conference on, pp. 1452-1457. IEEE, 2017.
[11] J. Fang, Y. Zhou, Y. Yu, and S. D. Du, "Fine-Grained Vehicle Model Recognition Using A Coarse-to-Fine Convolutional Neural Network Architecture", IEEE Transactions on Intelligent Transportation Systems, vol. 18, no. 7, pp. 1782-1792, 2017.
[12] Q. C. Hu, H. B. Wang, T. Li, and C. H. Shen, "Deep CNNs With Spatially Weighted Pooling for Fine-Grained Car Recognition", IEEE Transactions on Intelligent Transportation Systems, vol. 18, no. 11, pp. 3147-3156, 2017.
[13] T. J. Xiao, Y. C. Xu, K. Y. Yang, J. X. Zhang, Y. X. Peng, and Z. Zhang, "The Application of Two-level Attention Models in Deep Convolutional Neural Network for Finegrained Image Classification", 2015 IEEE Conference on Computer Vision and Pattern Recognition (Cvpr), pp. 842-850, 2015.
[14] C. Goring, E. Rodner, A. Freytag, and J. Denzler, "Nonparametric Part Transfer for Fine-grained Recognition", 2014 IEEE Conference on Computer Vision and Pattern Recognition, pp. 2489-2496, 2014.
[15] M. Stark et al., "Fine-Grained Categorization for 3D Scene Understanding", Proceedings of the British Machine Vision Conference 2012, 2012.
[16] L. Liao, R. M. Hu, J. Xiao, Q. Wang, J. Xiao, and J. Chen, "Exploiting Effects of Parts in Fine-Grained Categorization of Vehicles", 2015 IEEE International Conference on Image Processing (Icip), pp. 745-749, 2015.
[17] S. Ioffe and C. Szegedy, "Batch normalization: Accelerating deep network training by reducing internal covariate shift. " International Conference on Machine Learning, pp. 448-456, 2015.
[18] Y. Jia et al., "Caffe: Convolutional architecture for fast feature embedding. " in Proceedings of the 22nd ACM international conference on Multimedia. ACM, pp. 675-678, 2014.
[19] M. Lin, Q. Chen, and S. Yan, "Network in network, " arXiv preprint arXiv:1312. 4400, 2013.
[20] L. van der Maaten, "Accelerating t-SNE using Tree-Based Algorithms", Journal of Machine Learning Research, vol. 15, pp. 3221-3245, 2014.
Citation statistics
Cited Times [WOS]:0   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
Identifierhttps://irepository.cuhk.edu.cn/handle/3EPUXD0A/1185
CollectionSchool of Science and Engineering
Affiliation
1.School of Computer and Information, Hefei University of Technology, Hefei, China
2.School of Science and Engineering, Chinese University of Hong Kong at Shenzhen, Shenzhen, China
First Author AffilicationSchool of Science and Engineering
Recommended Citation
GB/T 7714
Yu, Y.,Jin, Q.,Wen Chen, C. FF-CMnet: A CNN-Based Model for Fine-Grained Classification of Car Models Based on Feature Fusion[J]. Proceedings - IEEE International Conference on Multimedia and Expo,2018.
APA Yu, Y., Jin, Q., & Wen Chen, C. (2018). FF-CMnet: A CNN-Based Model for Fine-Grained Classification of Car Models Based on Feature Fusion. Proceedings - IEEE International Conference on Multimedia and Expo.
MLA Yu, Y.,et al."FF-CMnet: A CNN-Based Model for Fine-Grained Classification of Car Models Based on Feature Fusion".Proceedings - IEEE International Conference on Multimedia and Expo (2018).
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