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Abstract
A first step in the process of automating weed removal in precision agriculture is the semantic segmentation of crops, weeds and soil. Deep learning techniques based on convolutional neural networks are successfully applied today and one of the most popular network architectures in semantic segmentation problems is U-Net. In this article, the variants in the U-Net architecture were evaluated based on the aggregation of residual and recurring blocks to improve their performance. For training and testing, a set of data available on the Internet was used, consisting of 60 multispectral images with unbalanced pixels, so techniques were applied to increase and balance the data. Experimental results show a slight increase in quality metrics compared to the classic U-Net architecture.
Original language | English |
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Title of host publication | Communications in Computer and Information Science |
Editors | Miguel Botto-Tobar, Marcelo Zambrano Vizuete, Pablo Torres-Carrión, Sergio Montes León, Guillermo Pizarro Vásquez, Benjamin Durakovic |
Publisher | Springer |
Pages | 473-485 |
Number of pages | 13 |
ISBN (Print) | 9783030425197 |
DOIs | |
State | Published - 1 Jan 2020 |
Event | 1st International Conference on Applied Technologies, ICAT 2019 - Quito, Ecuador Duration: 3 Dec 2019 → 5 Dec 2019 |
Publication series
Name | Communications in Computer and Information Science |
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Volume | 1194 CCIS |
ISSN (Print) | 1865-0929 |
ISSN (Electronic) | 1865-0937 |
Conference
Conference | 1st International Conference on Applied Technologies, ICAT 2019 |
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Country/Territory | Ecuador |
City | Quito |
Period | 3/12/19 → 5/12/19 |
Keywords
- Convolutional neural network
- Deep learning
- Precision agriculture
- Semantic segmentation
- U-Net
COAR
- Conference Object
OECD Category
- Ingeniería de sistemas y comunicaciones
Ulima Repository Subject
- Agricultura
- Agriculture
- Artificial neural networks
- Automation
- Automatización
- Redes neuronales artificiales
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Dive into the research topics of 'Semantic Segmentation of Weeds and Crops in Multispectral Images by Using a Convolutional Neural Networks Based on U-Net'. Together they form a unique fingerprint.Projects
- 1 Finished
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Quinua Smartapp: Quinoa Smartapp: intelligent rural platform prototype, in real time, to increase productivity in the organic quinoa value chain (chenopodium quinoa willd)
Bedón Monzón, H. M., Garcia Lopez, Y. J., Carhuancho Lucen, C. A. & Jimenez Davalos, J. E.
6/01/17 → 4/12/19
Project: Research