@inproceedings{0b87169a8e174e549a927c9a13717302,
title = "Deep Learning for Scene Recognition from Visual Data: A Survey",
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.",
keywords = "Computer Vision, Scene Recognition, Ensemble Techniques, Deep Learning",
author = "Alina Matei and Andreea Glavan and {Talavera Mart{\'i}nez}, Estefan{\'i}a",
year = "2020",
doi = "10.1007/978-3-030-61705-9_64",
language = "English",
isbn = "978-3-030-61704-2",
series = "Lecture Notes in Computer Science ",
publisher = "Springer",
pages = "763--773",
editor = "{de la Cal}, {Enrique Antonio } and {Villar Flecha}, {Jos{\'e} Ram{\'o}n } and Corchado, {Emilio }",
booktitle = "Hybrid Artificial Intelligent Systems",
note = "15th International Conference, HAIS 2020 ; Conference date: 11-11-2020 Through 13-11-2020",
}