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      Bayesian retinex underwater image enhancement

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      Engineering Applications of Artificial Intelligence
      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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            Image-to-Image Translation with Conditional Adversarial Networks

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              Distinctive Image Features from Scale-Invariant Keypoints

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                Author and article information

                Contributors
                Journal
                Engineering Applications of Artificial Intelligence
                Engineering Applications of Artificial Intelligence
                Elsevier BV
                09521976
                May 2021
                May 2021
                : 101
                : 104171
                Article
                10.1016/j.engappai.2021.104171
                aa1176d9-840f-43a4-bf6a-e30f8b394513
                © 2021

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

                https://doi.org/10.15223/policy-017

                https://doi.org/10.15223/policy-037

                https://doi.org/10.15223/policy-012

                https://doi.org/10.15223/policy-029

                https://doi.org/10.15223/policy-004

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