Exploring deep learning techniques for illuminance estimation

Abstract In recent years, deep learning techniques had a revolutionary impact on several domains, including computer vision and image processing. This research paper focuses on exploring deep learning methods to achieve precise illuminance estimation, which holds significant importance in applicatio...

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Bibliographic Details
Published in:Expert systems 2024-02
Main Authors: Vélez Bedoya, Jairo Iván, González Bedia, Manuel, Ossa, Luis Fernando Castillo, Arango‐López, Jeferson, Díaz‐Arancibia, Jaime
Format: Article
Language:English
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Summary:Abstract In recent years, deep learning techniques had a revolutionary impact on several domains, including computer vision and image processing. This research paper focuses on exploring deep learning methods to achieve precise illuminance estimation, which holds significant importance in applications such as augmented reality, virtual reality, and photography. However, accurately estimating illuminance in complex scenes continues to pose challenges due to the intricate interplay between light sources, objects, and surfaces. The results of extensive experimentation demonstrate the immense potential of deep learning techniques in illuminance estimation. These techniques exhibit promising accuracy and robustness, enabling them to handle diverse scenarios effectively. The valuable insights derived from this study can serve as a guiding framework for future research endeavours and contribute to the development of efficient and precise methodologies for illuminance estimation across a wide range of practical applications.
ISSN:0266-4720
1468-0394
DOI:10.1111/exsy.13559