|
|
|
|
LEADER |
01000naa a22002652 4500 |
001 |
NLM345036271 |
003 |
DE-627 |
005 |
20231226024143.0 |
007 |
cr uuu---uuuuu |
008 |
231226s2022 xx |||||o 00| ||eng c |
024 |
7 |
|
|a 10.1016/j.wasman.2022.08.007
|2 doi
|
028 |
5 |
2 |
|a pubmed24n1150.xml
|
035 |
|
|
|a (DE-627)NLM345036271
|
035 |
|
|
|a (NLM)35985078
|
035 |
|
|
|a (PII)S0956-053X(22)00409-3
|
040 |
|
|
|a DE-627
|b ger
|c DE-627
|e rakwb
|
041 |
|
|
|a eng
|
100 |
1 |
|
|a Moral, Paula
|e verfasserin
|4 aut
|
245 |
1 |
0 |
|a Towards automatic waste containers management in cities via computer vision
|b containers localization and geo-positioning in city maps
|
264 |
|
1 |
|c 2022
|
336 |
|
|
|a Text
|b txt
|2 rdacontent
|
337 |
|
|
|a ƒaComputermedien
|b c
|2 rdamedia
|
338 |
|
|
|a ƒa Online-Ressource
|b cr
|2 rdacarrier
|
500 |
|
|
|a Date Completed 07.09.2022
|
500 |
|
|
|a Date Revised 07.09.2022
|
500 |
|
|
|a published: Print-Electronic
|
500 |
|
|
|a Citation Status MEDLINE
|
520 |
|
|
|a Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.
|
520 |
|
|
|a This paper describes the scientific achievements of a collaboration between a research group and the waste management division of a company. While these results might be the basis for several practical or commercial developments, we here focus on a novel scientific contribution: a methodology to automatically generate geo-located waste container maps. It is based on the use of Computer Vision algorithms to detect waste containers and identify their geographic location and dimensions. Algorithms analyze a video sequence and provide an automatic discrimination between images with and without containers. More precisely, two state-of-the-art object detectors based on deep learning techniques have been selected for testing, according to their performance and to their adaptability to an on-board real-time environment: EfficientDet and YOLOv5. Experimental results indicate that the proposed visual model for waste container detection is able to effectively operate with consistent performance disregarding the container type (organic waste, plastic, glass and paper recycling,…) and the city layout, which has been assessed by evaluating it on eleven different Spanish cities that vary in terms of size, climate, urban layout and containers' appearance
|
650 |
|
4 |
|a Journal Article
|
650 |
|
4 |
|a Computer Vision
|
650 |
|
4 |
|a Deep Learning
|
650 |
|
4 |
|a Object detection
|
650 |
|
4 |
|a Waste container localization
|
650 |
|
7 |
|a Plastics
|2 NLM
|
700 |
1 |
|
|a García-Martín, Álvaro
|e verfasserin
|4 aut
|
700 |
1 |
|
|a Escudero-Viñolo, Marcos
|e verfasserin
|4 aut
|
700 |
1 |
|
|a Martínez, José M
|e verfasserin
|4 aut
|
700 |
1 |
|
|a Bescós, Jesús
|e verfasserin
|4 aut
|
700 |
1 |
|
|a Peñuela, Jesús
|e verfasserin
|4 aut
|
700 |
1 |
|
|a Martínez, Juan Carlos
|e verfasserin
|4 aut
|
700 |
1 |
|
|a Alvis, Gonzalo
|e verfasserin
|4 aut
|
773 |
0 |
8 |
|i Enthalten in
|t Waste management (New York, N.Y.)
|d 1999
|g 152(2022) vom: 16. Okt., Seite 59-68
|w (DE-627)NLM098197061
|x 1879-2456
|7 nnns
|
773 |
1 |
8 |
|g volume:152
|g year:2022
|g day:16
|g month:10
|g pages:59-68
|
856 |
4 |
0 |
|u http://dx.doi.org/10.1016/j.wasman.2022.08.007
|3 Volltext
|
912 |
|
|
|a GBV_USEFLAG_A
|
912 |
|
|
|a SYSFLAG_A
|
912 |
|
|
|a GBV_NLM
|
912 |
|
|
|a GBV_ILN_350
|
951 |
|
|
|a AR
|
952 |
|
|
|d 152
|j 2022
|b 16
|c 10
|h 59-68
|