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Author (up) Ángel Morera, Ángel Sánchez, A. Belén Moreno, Angel D. Sappa, & José F. Vélez pdf  isbn
openurl 
  Title SSD vs. YOLO for Detection of Outdoor Urban Advertising Panels under Multiple Variabilities. Type Journal Article
  Year 2020 Publication Abbreviated Journal In Sensors  
  Volume Vol. 2020-August Issue 16 Pages pp. 1-23  
  Keywords object detection; urban outdoor panels; one-stage detectors; Single Shot MultiBox Detector (SSD); You Only Look Once (YOLO); detection metrics; object and scene imaging variabilities  
  Abstract This work compares Single Shot MultiBox Detector (SSD) and You Only Look Once (YOLO)

deep neural networks for the outdoor advertisement panel detection problem by handling multiple

and combined variabilities in the scenes. Publicity panel detection in images o ers important

advantages both in the real world as well as in the virtual one. For example, applications like Google

Street View can be used for Internet publicity and when detecting these ads panels in images, it could

be possible to replace the publicity appearing inside the panels by another from a funding company.

In our experiments, both SSD and YOLO detectors have produced acceptable results under variable

sizes of panels, illumination conditions, viewing perspectives, partial occlusion of panels, complex

background and multiple panels in scenes. Due to the diculty of finding annotated images for the

considered problem, we created our own dataset for conducting the experiments. The major strength

of the SSD model was the almost elimination of False Positive (FP) cases, situation that is preferable

when the publicity contained inside the panel is analyzed after detecting them. On the other side,

YOLO produced better panel localization results detecting a higher number of True Positive (TP)

panels with a higher accuracy. Finally, a comparison of the two analyzed object detection models

with di erent types of semantic segmentation networks and using the same evaluation metrics is

also included.
 
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 14248220 Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number cidis @ cidis @ Serial 133  
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Author (up) Angel Morera; Angel Sánchez; Angel D. Sappa; José F. Vélez pdf  openurl
  Title Robust Detection of Outdoor Urban Advertising Panels in Static Images. Type Conference Article
  Year 2019 Publication 17th International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS 2019); Ávila, España. Communications in Computer and Information Science Abbreviated Journal  
  Volume 1047 Issue Pages 246-256  
  Keywords  
  Abstract One interesting publicity application for Smart City environments is recognizing brand information contained in urban advertising

panels. For such a purpose, a previous stage is to accurately detect and

locate the position of these panels in images. This work presents an effective solution to this problem using a Single Shot Detector (SSD) based

on a deep neural network architecture that minimizes the number of

false detections under multiple variable conditions regarding the panels and the scene. Achieved experimental results using the Intersection

over Union (IoU) accuracy metric make this proposal applicable in real

complex urban images.
 
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number gtsi @ user @ Serial 107  
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