CloudA: A Ground-Based Cloud Classification Method with a Convolutional Neural Network

[1]  Maneesha Singh,et al.  Automated ground-based cloud recognition , 2005, Pattern Analysis and Applications.

[2]  Chong-wei Zheng,et al.  Rezoning global offshore wind energy resources , 2018, Renewable Energy.

[3]  Geoffrey E. Hinton,et al.  ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.

[4]  Josep Calbó,et al.  Feature Extraction from Whole-Sky Ground-Based Images for Cloud-Type Recognition , 2008 .

[5]  Jun Yang,et al.  From pixels to patches: a cloud classification method based on a bag of micro-structures , 2015 .

[6]  Andreas Kazantzidis,et al.  Cloud observations in Switzerland using hemispherical sky cameras , 2015 .

[7]  George Economou,et al.  Cloud detection and classification with the use of whole-sky ground-based images , 2012 .

[8]  Qing Wang,et al.  Source Tracing of the Swell Energy: A Case Study of the Pacific Ocean , 2019, IEEE Access.

[9]  Apichat Heednacram,et al.  Feature extraction techniques for ground-based cloud type classification , 2015, Expert Syst. Appl..

[10]  Zhao Shi-jun.  Classification of Whole Sky Infrared Cloud Image Based on the LBP Operator , 2009 .

[11]  A. Heinle,et al.  Automatic cloud classification of whole sky images , 2010 .

[12]  Jimmy Ba,et al.  Adam: A Method for Stochastic Optimization , 2014, ICLR.

[13]  Stefan Winkler,et al.  Categorization of cloud image patches using an improved texton-based approach , 2015, 2015 IEEE International Conference on Image Processing (ICIP).