Deep learning for scene recognition from visual data: a survey

Alina Matei, Andreea Glavan, Estefanía Talavera Martínez

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    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 publicationLecture Notes in Artificial Intelligence
    Subtitle of host publicationLNAI-LNCS
    PublisherarXiv
    Publication statusSubmitted - 2020
    EventInternational Conference on Hybrid Artificial Intelligence Systems -
    Duration: 11-Nov-2020 → …
    http://2020.haisconference.eu/

    Conference

    ConferenceInternational Conference on Hybrid Artificial Intelligence Systems
    Abbreviated titleHAIS2020
    Period11/11/2020 → …
    Internet address

    Keywords

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

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