A wavelet-based remote sensing image coding for noisy channels

2009 ◽  
Author(s):  
Jiaji Wu ◽  
Jingchun Qi ◽  
Licheng Jiao ◽  
Guangming Shi
2014 ◽  
Vol 41 (6) ◽  
pp. 0614001
Author(s):  
张立保 Zhang Libao ◽  
丘兵昌 Qiu Bingchang ◽  
杨绪业 Yang Xuye ◽  
赵慧刚 Zhao Huigang

2010 ◽  
Author(s):  
Juan Muñoz-Gómez ◽  
Joan Bartrina-Rapesta ◽  
Ian Blanes ◽  
Leandro Jiménez-Rodríguez ◽  
Francesc Aulí-Llinàs ◽  
...  

Author(s):  
Stefano Baronti ◽  
Cinzia Lastri ◽  
Bruno Aiazzi

Author(s):  
Sumit Kaur

Abstract- Deep learning is an emerging research area in machine learning and pattern recognition field which has been presented with the goal of drawing Machine Learning nearer to one of its unique objectives, Artificial Intelligence. It tries to mimic the human brain, which is capable of processing and learning from the complex input data and solving different kinds of complicated tasks well. Deep learning (DL) basically based on a set of supervised and unsupervised algorithms that attempt to model higher level abstractions in data and make it self-learning for hierarchical representation for classification. In the recent years, it has attracted much attention due to its state-of-the-art performance in diverse areas like object perception, speech recognition, computer vision, collaborative filtering and natural language processing. This paper will present a survey on different deep learning techniques for remote sensing image classification. 


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