Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Izar Azpiroz"'
Publikováno v:
Applied Sciences, Vol 13, Iss 19, p 10987 (2023)
Similarly efficient feature groups occur in prediction procedures such as Olive phenology forecasting. This study proposes a procedure that can be used to extract the most representative feature grouping from Market Basket Analysis-derived methodolog
Externí odkaz:
https://doaj.org/article/f43c62d8a8ee49ad97aa05cc41a18cbd
Autor:
Álvaro Gutiérrez, Patricia Blanco, Verónica Ruiz, Christos Chatzigeorgiou, Xabier Oregui, Marta Álvarez, Sara Navarro, Michalis Feidakis, Izar Azpiroz, Gemma Izquierdo, Blanca Larraga-García, Panagiotis Kasnesis, Igor García Olaizola, Federico Álvarez
Publikováno v:
Applied Sciences, Vol 13, Iss 13, p 7368 (2023)
During the last decade, new technological tools have emerged to provide first responders with augmented senses in emergency and disaster situations. Some of these tools focus on providing extra information about their surroundings. However, despite a
Externí odkaz:
https://doaj.org/article/d89114832a0046898a94f7d753c1fa06
Publikováno v:
Applied Sciences, Vol 13, Iss 9, p 5499 (2023)
This paper presents a Deep Learning (DL) and Image-Processing (IP) pipeline that addresses exposure recovery in challenging lighting conditions for enhancing First Responders’ (FRs) Situational Awareness (SA) during rescue operations. The method ai
Externí odkaz:
https://doaj.org/article/1f0a9c3eaa6a42bfb8c4555676024659
Publikováno v:
Sensors, Vol 20, Iss 21, p 6381 (2020)
Knowledge of phenological events and their variability can help to determine final yield, plan management approach, tackle climate change, and model crop development. THe timing of phenological stages and phases is known to be highly correlated with
Externí odkaz:
https://doaj.org/article/d863707c4f1949c5972296ac90fdc00f
Akademický článek
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Autor:
Álvarez, Álvaro Gutiérrez, Patricia Blanco, Verónica Ruiz, Christos Chatzigeorgiou, Xabier Oregui, Marta Álvarez, Sara Navarro, Michalis Feidakis, Izar Azpiroz, Gemma Izquierdo, Blanca Larraga-García, Panagiotis Kasnesis, Igor García Olaizola, Federico
Publikováno v:
Applied Sciences; Volume 13; Issue 13; Pages: 7368
During the last decade, new technological tools have emerged to provide first responders with augmented senses in emergency and disaster situations. Some of these tools focus on providing extra information about their surroundings. However, despite a
Autor:
D. Alda, Izar Azpiroz, U. Otamendi, X. Garitano, F.J. Perez, Igor G. Olaizola, Marco Quartulli
Publikováno v:
IGARSS
We propose a methodology to manage and process remote sensing and geo-imagery data for non-expert users. The proposed system provides automated data ingestion and manipulation capability for analytical data-driven purposes. In this paper, we describe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::29e59c7f2cd1ac8cfed87f21ebdec708
http://arxiv.org/abs/2210.01470
http://arxiv.org/abs/2210.01470
Publikováno v:
Sensors
Volume 20
Issue 21
Sensors (Basel, Switzerland)
Sensors, Vol 20, Iss 6381, p 6381 (2020)
Volume 20
Issue 21
Sensors (Basel, Switzerland)
Sensors, Vol 20, Iss 6381, p 6381 (2020)
Knowledge of phenological events and their variability can help to determine final yield, plan management approach, tackle climate change, and model crop development. THe timing of phenological stages and phases is known to be highly correlated with
Publikováno v:
Journal of Computational Physics
Journal of Computational Physics, Elsevier, 2020, 419, ⟨10.1016/j.jcp.2020.109683⟩
Journal of Computational Physics, 2020, 419, ⟨10.1016/j.jcp.2020.109683⟩
Journal of Computational Physics, Elsevier, 2020, 419, ⟨10.1016/j.jcp.2020.109683⟩
Journal of Computational Physics, 2020, 419, ⟨10.1016/j.jcp.2020.109683⟩
International audience; A new computational strategy is proposed for determining all elastic scatterer characteristics including the shape, the material properties (Lamé coefficients and density), and the location from the knowledge of far-field pat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fe94e73fffd2801db34809fa0a22af5b
https://hal.inria.fr/hal-02961043
https://hal.inria.fr/hal-02961043
Publikováno v:
2020 Global Internet of Things Summit (GIoTS)
GIoTS
GIoTS
Several methods based on regression techniques are used for the prediction of phenological phases in modern olive growing. This study collects phenological observations and agrometeorological data for several Italian provinces. The aim of the analysi