Semi-supervised learning on large-scale geotagged photos for situation recognition

Journal of Visual Communication and Image Representation

Volumn 48, Issue , 2017, Pages 310-316

  Tang, Mengfan ^a   Nie, Feiping ^b   Pongpaichet, Siripen ^c   Jain, Ramesh ^a  

^a Irvine   (United States)

^b NORTHWESTERN POLYTECHNICAL UNIVERSITY   (China)

^c MAHIDOL UNIVERSITY   (Thailand)

Author keywords

Capped norm; Evolving situations; New label discovery; Outlier elimination; Semi supervised learning; 1 norm

Indexed keywords

DEEP LEARNING; EDUCATION; STATISTICS;

CAPPED NORM; EVOLVING SITUATIONS; NEW LABEL DISCOVERY; OUTLIER ELIMINATION; SEMI- SUPERVISED LEARNING;

SUPERVISED LEARNING;

EID: 85026440117     PISSN: 10473203     EISSN: 10959076     Source Type: Journal    
DOI: 10.1016/j.jvcir.2017.07.005     Document Type: Article

References (27)

1. Endsley, M.R., Situation awareness global assessment technique (SAGAT). IEEE Aerospace and Electronics Conference, 1988.
2. Tang, M., Pongpaichet, S., Jain, R., Research challenges in developing multimedia systems for managing emergency situations. Proceedings of the 2016 ACM on Multimedia Conference, 2016, ACM, 938–947.
3. Tang, M., Wu, X., Agrawal, P., Pongpaichet, S., Jain, R., Integration of diverse data sources for spatial pm2. 5 data interpolation. IEEE Trans. Multimedia 19:2 (2017), 408–417.
4. Jain, R., Let's weave the visual web. MultiMedia, IEEE 22:3 (2015), 66–72.
5. Pongpaichet, S., Tang, M., Jalali, L., Jain, R., Using photos as micro-reports of events. ICMR, 2016.
6. Lu, X., Li, X., Multiresolution imaging. IEEE Trans. Cybernet. 44:1 (2014), 149–160.
7. Lu, X., Li, X., Mou, L., Semi-supervised multitask learning for scene recognition. IEEE Trans. Cybernet. 45:9 (2015), 1967–1976.
8. Lu, X., Yuan, Y., Yan, P., Image super-resolution via double sparsity regularized manifold learning. IEEE Trans. Circ. Syst. Video Technol. 23:12 (2013), 2022–2033.
9. Lu, X., Yuan, Y., Zheng, X., Jointly dictionary learning for change detection in multispectral imagery. IEEE Trans. Cybernet. 47:4 (2017), 884–897.
10. Lu, X., Zheng, X., Li, X., Latent semantic minimal hashing for image retrieval. IEEE Trans. Image Process. 26:1 (2017), 355–368.
11. Wang, Y., Kankanhalli, M.S., Tweeting cameras for event detection. WWW, 2015.
12. Jin, X., Gallagher, A., Cao, L., Luo, J., Han, J., The wisdom of social multimedia: using Flickr for prediction and forecast. ACM Multimedia, 2010.
13. N. Hochman, L. Manovich, Zooming into An Instagram City: Reading the Local through Social Media, First Monday 18 (7). URL < http://firstmonday.org/ojs/index.php/fm/article/view/4711>.
14. Chang, S.-F., Ellis, D., Jiang, W., Lee, K., Yanagawa, A., Loui, A.C., Luo, J., Large-scale multimodal semantic concept detection for consumer video. Proceedings of the International Workshop on Multimedia Information Retrieval, 2007, ACM, 255–264.
15. Tang, J., Hong, R., Yan, S., Chua, T.-S., Qi, G.-J., Jain, R., Image annotation by k nn-sparse graph-based label propagation over noisily tagged web images. ACM TIST, 2(2), 2011, 14.
16. Wang, M., Fu, W., Hao, S., Liu, H., Wu, X., Learning on big graph: label inference and regularization with anchor hierarchy. IEEE Trans. Knowl. Data Eng. 29:5 (2017), 1101–1114.
17. Wang, M., Fu, W., Hao, S., Tao, D., Wu, X., Scalable semi-supervised learning by efficient anchor graph regularization. IEEE Trans. Knowl. Data Eng. 28:7 (2016), 1864–1877.
18. Zhu, X., Ghahramani, Z., Lafferty, J., et al. Semi-supervised learning using gaussian fields and harmonic functions. ICML, 2003.
19. Tang, M., Nie, F., Jain, R., A graph regularized dimension reduction method for out-of-sample data. Neurocomputing 225 (2017), 58–63.
20. Yang, M., Zhang, L., Yang, J., Zhang, D., Robust sparse coding for face recognition. CVPR, 2011.
21. Ye, G., Tang, M., Cai, J.-F., Nie, Q., Xie, X., Low-rank regularization for learning gene expression programs. PloS One, 8(12), 2013, e82146.
22. Tang, M., Agrawal, P., Nie, F., Pongpaichet, S., Jain, R., A graph based multimodal geospatial interpolation framework. 2016 IEEE International Conference on Multimedia and Expo (ICME), 2016, IEEE, 1–6.
23. Nie, F., Xiang, S., Liu, Y., Zhang, C., A general graph-based semi-supervised learning with novel class discovery. Neural Comput. Appl. 19:4 (2010), 549–555.
24. Tang, M., Nie, F., Jain, R., Capped lp-norm graph embedding for photo clustering. ACM Multimedia, 2016.
25. Nie, F., Wang, X., Jordan, M.I., Huang, H., The constrained Laplacian rank algorithm for graph-based clustering. AAAI, 2016.
26. Nie, F., Yuan, J., Huang, H., Optimal mean robust principal component analysis. ICML, 2014.
27. Thomee, B., Elizalde, B., Shamma, D.A., Ni, K., Friedland, G., Poland, D., Borth, D., Li, L.-J., YFCC100M: the new data in multimedia research. Commun. ACM 59:2 (2016), 64–73.