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      Shark detection and classification with machine learning

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      Ecological Informatics
      Elsevier BV

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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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            Dropout: A Simple Way to Prevent Neural Networks from Overfitting.

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              The measurement of diversity in different types of biological collections

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                Author and article information

                Journal
                Ecological Informatics
                Ecological Informatics
                Elsevier BV
                15749541
                July 2022
                July 2022
                : 69
                : 101673
                Article
                10.1016/j.ecoinf.2022.101673
                1b77bc5c-a489-467b-bb7c-05f0f468ebdb
                © 2022

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

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