Deep Learning for Scene Recognition from Visual Data: A Survey

Alina Matei, Andreea Glavan, Estefanía Talavera Martínez

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    13 Citations (Scopus)
    203 Downloads (Pure)

    Abstract

    The use of deep learning techniques has exploded during the last few years, resulting in a direct contribution to the field of artificial intelligence. This work aims to be a review of the state-of-the-art in scene recognition with deep learning models from visual data. Scene recognition is still an emerging field in computer vision, which has been addressed from a single image and dynamic image perspective. We first give an overview of available datasets for image and video scene recognition. Later, we describe ensemble techniques introduced by research papers in the field. Finally, we give some remarks on our findings and discuss what we consider challenges in the field and future lines of research. This paper aims to be a future guide for model selection for the task of scene recognition.
    Original languageEnglish
    Title of host publicationHybrid Artificial Intelligent Systems
    EditorsEnrique Antonio de la Cal, José Ramón Villar Flecha, Emilio Corchado
    PublisherSpringer
    Pages763-773
    Number of pages11
    ISBN (Electronic)978-3-030-61705-9
    ISBN (Print)978-3-030-61704-2
    DOIs
    Publication statusPublished - 2020
    Event15th International Conference, HAIS 2020 - Gijón, Spain
    Duration: 11-Nov-202013-Nov-2020

    Publication series

    NameLecture Notes in Computer Science
    PublisherSpringer
    Volume12344

    Conference

    Conference15th International Conference, HAIS 2020
    Country/TerritorySpain
    CityGijón
    Period11/11/202013/11/2020

    Keywords

    • Computer Vision
    • Scene Recognition
    • Ensemble Techniques
    • Deep Learning

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