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A Review About Machine and Deep Learning Approaches for Intelligent User Interfaces

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Advanced Information Networking and Applications (AINA 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 451))

Abstract

The last few years have seen a huge explosion in the use of Machine Learning (ML)-based approaches, particularly Deep Neural Networks (DNNs) in a variety of fields, to solve complex prediction problems, or in industry to provide a very effective predictive maintenance system for equipment, or in the field of image manipulation and computer vision. In addition, recent publications have contributed to the evolution of Intelligent User Interfaces (IUIs) through DNN-based approaches. This paper aims to share a recent overview of published work on the development of IUIs, initially through ML techniques and then, analyze only those based on DNN models. The ultimate goal is to provide researchers with concrete support to be able to develop IUI projects and to be able to inform them about the latest developments on Artificial Intelligence (AI) models used in this field.

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Acknowledgments

This paper has been produced with the financial support of the Justice Programme of the European Union, 101046629 CREA2, JUST-2021-EJUSTICE, JUST2027 Programme. The contents of this report are the sole responsibility of the authors and can in no way be taken to reflect the views of the European Commission.

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Correspondence to Antonino Ferraro .

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Ferraro, A., Giacalone, M. (2022). A Review About Machine and Deep Learning Approaches for Intelligent User Interfaces. In: Barolli, L., Hussain, F., Enokido, T. (eds) Advanced Information Networking and Applications. AINA 2022. Lecture Notes in Networks and Systems, vol 451. Springer, Cham. https://doi.org/10.1007/978-3-030-99619-2_9

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