Deep neural networks for precipitation estimation from remotely sensed information

2016 IEEE Congress on Evolutionary Computation, CEC 2016

Volumn , Issue , 2016, Pages 1349-1355

  Tao, Yumeng ^a   Gao, Xiaogang ^a   Ihler, Alexander ^b   Hsu, Kuolin ^a   Sorooshian, Soroosh ^a  

^a University of California at Irvine   (United States)

^b Irvine   (United States)

Author keywords

Deep neural networks; Kullback Leibler divergence; Precipitation; Remote sensing; Stacked denoising auto encoders

Indexed keywords

LEARNING SYSTEMS; PRECIPITATION (CHEMICAL); REMOTE SENSING;

AUTO ENCODERS; DEEP NEURAL NETWORKS; KULLBACK LEIBLER DIVERGENCE; OBJECTIVE FUNCTIONS; OPERATIONAL PRODUCTS; PRECIPITATION DATA; PRECIPITATION ESTIMATION; PRECIPITATION ESTIMATION FROM REMOTELY SENSED INFORMATION;

PRECIPITATION (METEOROLOGY);

EID: 85008254124     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CEC.2016.7743945     Document Type: Conference Paper

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