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COMPARATIVE STUDY ON DEEP NEURAL NETWORK MODELS FOR CROP CLASSIFICATION USING TIME SERIES POLSAR AND OPTICAL DATA
Deep neural networks CNNs LSTMs ConvLSTMs Crop classification
2019/2/28
Crop classification is an important task in many crop monitoring applications. Satellite remote sensing has provided easy, reliable, and fast approaches to crop classification task. In this study, a c...
广东外语外贸大学运筹学英文课件第八章 Network Models。
Towards a Better Understanding of Large Scale Network Models
Better Understanding Large Scale Network Models
2011/3/4
Connectivity and capacity are two fundamental properties of wireless multi-hop networks. The scalability of these properties has been a primary concern for which asymptotic analysis is a useful tool.
Data transformation for neural network models in water resources applications
Data transformation neural network models water resources applications
2009/12/4
A step that should be considered when developing artificial neural network (ANN) models for water resources applications is the selection of an appropriate transformation of the data. In general, the ...
Clustering of heterogeneous precipitation fields for the assessment and possible improvement of lumped neural network models for streamflow forecasts
rainfall-runoff Clustering
2009/5/13
This work addresses the issue of better considering the heterogeneity of precipitation fields within lumped rainfall-runoff models where only areal mean precipitation is usually used as an input. A me...
NEURAL NETWORK MODELS FOR DESIGN OF BLOCK CIPHER SYSTEM
Block cipher system Hopfield neural net
2007/8/7
In this paper, a class of block cipher systems having asymptotically perfect secrecy is constructed by using the neural network models modified from the Hopfield model.