scholarly journals FPGA Implementation of JPEG-LS Remote Sensing Image Coding Algorithm

2018 ◽  
Author(s):  
Hairong Wang
Keyword(s):  
Remote Sensing ◽  
Image Coding ◽  
Remote Sensing Image ◽  
Fpga Implementation

Remote Sensing Image Coding Based on Direction Optimal Lifting Strategy

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
Keyword(s):  
Remote Sensing ◽  
Image Coding ◽  
Remote Sensing Image

4D remote sensing image coding with JPEG2000

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

Remote-Sensing Image Coding

2006 ◽  
pp. 389-411 ◽  
Author(s):  
Stefano Baronti ◽  
Cinzia Lastri ◽  
Bruno Aiazzi
Keyword(s):  
Remote Sensing ◽  
Image Coding ◽  
Remote Sensing Image

A wavelet-based remote sensing image coding for noisy channels

2009 ◽  
Author(s):  
Jiaji Wu ◽  
Jingchun Qi ◽  
Licheng Jiao ◽  
Guangming Shi
Keyword(s):  
Remote Sensing ◽  
Image Coding ◽  
Remote Sensing Image ◽  
Noisy Channels

Deep Learning Based High-Resolution Remote Sensing Image classification

2017 ◽  
Vol 7 (10) ◽  
pp. 22
Author(s):  
Sumit Kaur
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Deep Learning ◽  
Image Classification ◽  
Language Processing ◽  
Object Perception ◽  
Remote Sensing Image ◽  
Research Area ◽  
Remote Sensing Image Classification ◽  
Unsupervised Algorithms

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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