A graph based multimodal geospatial interpolation framework

Proceedings - IEEE International Conference on Multimedia and Expo

Volumn 2016-August, Issue , 2016, Pages

  Tang, Mengfan ^a   Agrawal, Pranav ^a   Nie, Feiping ^a   Pongpaichet, Siripen ^a   Jain, Ramesh ^a  

^a NONE

Author keywords

Air pollution; Graph based model; Interpolation; Multimodal data; Spatial Gaussian Process; Spectral analysis

Indexed keywords

AIR POLLUTION; INTERPOLATION; POLLUTION; SPECTRUM ANALYSIS;

ACCURATE PREDICTION; GAUSSIAN PROCESSES; GEOSPATIAL INTERPOLATIONS; GRAPH-BASED MODELING; MULTI-MODAL DATA; MULTIMEDIA RESEARCH; MULTIPLE RESOLUTIONS; SPATIAL INTERPOLATION;

GRAPHIC METHODS;

EID: 84987653365     PISSN: 19457871     EISSN: 1945788X     Source Type: Conference Proceeding    
DOI: 10.1109/ICME.2016.7552968     Document Type: Conference Paper

References (20)

1. S. Pongpaichet, V. K. Singh, M. Gao, and R. Jain, "EventShop: recognizing situations in web data streams," in Proc. 22nd Int. Conf. WWW. International World Wide Web Conferences Steering Committee
2. M. Tang, P. Agrawal, S. Pongpaichet, and R. Jain, "Geospatial interpolation analytics for data streams in eventshop," in Multimedia Expo. ICME, 2015 IEEE Int. Conf. IEEE
3. R. Durichen, M.A.F. Pimentel, L. Clifton, A. Schweikard, and D.A. Clifton, "Multitask gaussian processes for multivariate physiological time-series analysis," IEEE T. BIO-MED. ENG., vol. 62, no. 1
4. M. A. Osborne, S. J. Roberts, A. Rogers, and N. R. Jennings, "Real-time information processing of environmental sensor network data using bayesian gaussian processes," ACM Trans. SE. NETW., vol. 9, no. 1
5. F. Hui, B. Xu, H. Huang, Q. Yu, and P. Gong, "Modelling spatial-temporal change of poyang lake using multitemporal landsat imagery," INT. J. REMOTE SENS., vol. 29, no. 20
6. N. J. McMillan, D. M. Holland, M. Morara, J. Feng, V. J. Berrocal, A. E. Gelfand, and D. M. Holland, "A spatio-temporal downscaler for output from numerical models," J. AGR. BIOL. ENVIR. ST., vol. 15, no. 2
7. V. J. Berrocal, A. E. Gelfand, and D. M. Holland, "A spatio-temporal downscaler for output from numerical models," J. AGR. BIOL. ENVIR. ST., vol. 15, no. 2
8. K. V. Mardia and RJ Marshall, "Maximum likelihood estimation of models for residual covariance in spatial regression," Biometrika, vol. 71, no. 1
9. M Tang, P Agrawal, and R Jain, "Habits vs environment: What really causes asthma?," arXiv preprint arXiv:1601.05141, 2016
10. E. V. Bonilla, K. M. Chai, and C. Williams, "Multi-task gaussian process prediction," in Adv. Neural Inf. Process Sys
11. M. Fuentes and A. E. Raftery, "Model evaluation and spatial interpolation by bayesian combination of observations with outputs from numerical models," Biometrics, vol. 61, no. 1
12. C. J. Paciorek, "Combining spatial information sources while accounting for systematic errors in proxies," J. R. STAT. SOC., vol. 61, no. 3
13. W Ping, Q Liu, and A Ihler, "Marginal structured SVM with hidden variables," in International Conference on Machine Learning, 2014
14. H. Nguyen, N. Cressie, and A. Braverman, "Spatial statistical data fusion for remote sensing applications," J. AM. STAT. ASSOC., vol. 107, no. 499
15. A. Van Donkelaar, R. V Martin, and R. J. Park, "Estimating ground-level PM2. 5 using aerosol optical depth determined from satellite remote sensing," J. GEOPHYS. RES-ATMOS., vol. 111
16. D. W. Byun, JKS Ching, et.al., Science algorithms of the EPA Models-3 community multiscale air quality (CMAQ) modeling system, US EPA, Office of Research and Development
17. "U-air: When urban air quality inference meets big data
18. X. Zhu, Z. Ghahramani, J. Lafferty, et. al., "Semisupervised learning using gaussian fields and harmonic functions," in Int. Conf. Machine Learning, vol. 3
19. Y. Xu, J. S. Dyer, and A. B. Owen, "Empirical stationary correlations for semi-supervised learning on graphs," ANN. APPL. STAT
20. H Chang, BJ Reich and K. Foley, "A spectral method for spatial downscaling," Biometrics, vol. 70, no. 4, pp. 932-942, 2014