Publications
2018
1.
Chaves, Deisy; Saikia, Surajit; Fernández-Robles, Laura; Alegre, Enrique; Trujillo, María
A systematic review on object localisation methods in images Artículo de revista
En: Revista Iberoamericana de Automática e Informática Industrial, vol. 15, no 3, pp. 231–242, 2018, (Publisher: UNIV POLITECNICA VALENCIA, EDITORIAL UPV CAMINO VERA SN, VALENCIA, 46022, SPAIN).
Resumen | Enlaces | BibTeX | Etiquetas: automated detection, Computer vision, deep learning, Faster-RCCN, image processing, Mask-RCNN, object localization, visual inspection
@article{chaves_systematic_2018,
title = {A systematic review on object localisation methods in images},
author = {Deisy Chaves and Surajit Saikia and Laura Fernández-Robles and Enrique Alegre and María Trujillo},
url = {https://polipapers.upv.es/index.php/RIAI/article/view/10229},
year = {2018},
date = {2018-01-01},
journal = {Revista Iberoamericana de Automática e Informática Industrial},
volume = {15},
number = {3},
pages = {231–242},
abstract = {This article provides a systematic review of methods for precise object localization in images, covering techniques from traditional sliding window methods (e.g., Viola-Jones) to modern deep learning-based approaches like Faster-RCNN and Mask-RCNN. It discusses the advantages, disadvantages, and applications of these methods in fields such as industrial inspection, clinical diagnosis, and obstacle detection in vehicles and robots. The review offers an organized summary of these techniques and highlights future research directions.},
note = {Publisher: UNIV POLITECNICA VALENCIA, EDITORIAL UPV CAMINO VERA SN, VALENCIA, 46022, SPAIN},
keywords = {automated detection, Computer vision, deep learning, Faster-RCCN, image processing, Mask-RCNN, object localization, visual inspection},
pubstate = {published},
tppubtype = {article}
}
This article provides a systematic review of methods for precise object localization in images, covering techniques from traditional sliding window methods (e.g., Viola-Jones) to modern deep learning-based approaches like Faster-RCNN and Mask-RCNN. It discusses the advantages, disadvantages, and applications of these methods in fields such as industrial inspection, clinical diagnosis, and obstacle detection in vehicles and robots. The review offers an organized summary of these techniques and highlights future research directions.