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      Progress of hyperspectral data processing and modelling for cereal crop nitrogen monitoring

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          Deep learning.

          Deep learning allows computational models that are composed of multiple processing layers to learn representations of data with multiple levels of abstraction. These methods have dramatically improved the state-of-the-art in speech recognition, visual object recognition, object detection and many other domains such as drug discovery and genomics. Deep learning discovers intricate structure in large data sets by using the backpropagation algorithm to indicate how a machine should change its internal parameters that are used to compute the representation in each layer from the representation in the previous layer. Deep convolutional nets have brought about breakthroughs in processing images, video, speech and audio, whereas recurrent nets have shone light on sequential data such as text and speech.
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              Support vector machines in remote sensing: A review

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                Author and article information

                Journal
                Computers and Electronics in Agriculture
                Computers and Electronics in Agriculture
                Elsevier BV
                01681699
                May 2020
                May 2020
                : 172
                : 105321
                Article
                10.1016/j.compag.2020.105321
                f26d958f-d56f-46c0-b06d-48cc09afd893
                © 2020

                https://www.elsevier.com/tdm/userlicense/1.0/

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