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DeepNEM: Deep Network Energy-Minimization for Agricultural Field Segmentation

Authors: Margarita Torre; Beatriz Remeseiro; Petia Radeva; Fernando Martinez;

DeepNEM: Deep Network Energy-Minimization for Agricultural Field Segmentation

Abstract

This work was supported in part by MINECO (Spanish Ministry of the Economy and Competitiveness) under Grant TIN2015-65069- C2-2-R, Grant TIN2017-89244-R, and Grant RTI2018-095232-B-C2 from the MINECO (Spanish Ministry of the Economy and Competitiveness); 2017SGR01742 (CVUB) and CERCA Programme from the Generalitat de Catalunya; and in part by the Principado de Asturias Regional Government, partially supported with EDRF funds under Grant IDI-2018-000176. The work of P.Radeva was supported by ICREA Academia 2014.

Keywords

:Matemàtiques i estadística::Investigació operativa::Programació matemàtica [Àrees temàtiques de la UPC], mathematical programming::90C Mathematical programming, Geophysics. Cosmic physics, :90 Operations research, mathematical programming::90C Mathematical programming [Classificació AMS], Operations research, Investigació operativa, region extraction, Classificació AMS::90 Operations research, mathematical programming::90B Operations research and management science, :90 Operations research, mathematical programming::90B Operations research and management science [Classificació AMS], Programació (Matemàtica), Àrees temàtiques de la UPC::Matemàtiques i estadística::Investigació operativa::Programació matemàtica, TC1501-1800, image segmentation, Classificació AMS::90 Operations research, Programming (Mathematics), QC801-809, Àrees temàtiques de la UPC::Matemàtiques i estadística::Investigació operativa::Optimització, Classificació AMS::90 Operations research, mathematical programming::90C Mathematical programming, Agricultural fields, Ocean engineering, mathematical programming::90B Operations research and management science, image edge analysis, :Matemàtiques i estadística::Investigació operativa::Optimització [Àrees temàtiques de la UPC]

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
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