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Ignacio Barrio

ResearcherPublications, citations & collaboration network

Ignacio Barrio is a researcher indexed in ScholarIQ from OpenAlex & ORCID. ScholarIQ records 29 works, 337 citations, an h-index of 10 and an i10-index of 10.

29
Works
337
Citations
10
h-index
10
i10-index

How has Ignacio Barrio's publication output changed over time?

ScholarIQpublication output · 2007–2024

Output grew100% over the shown period — from 1 works in 2007 to 2 in 2024.

1
1
5
1
2
20072018202120222024

What are the most-cited papers on Ignacio Barrio?

ScholarIQmost cited works
vitisBerry: An Android-smartphone application to early evaluate the number of grapevine berries by means of image analysis
Arturo Aquino, Ignacio Barrio, María P. Diago, Borja Millán, Javier Tardáguila
Computers and Electronics in Agriculture. 201869 CitationsOPEN ACCESS
Deep learning for the differentiation of downy mildew and spider mite in grapevine under field conditions
Salvador Gutiérrez, Inés Hernández, Sara Ceballos, Ignacio Barrio, Ana María Díez-Navajas, Javier Tardáguila
Computers and Electronics in Agriculture. 202163 Citations
Monitoring and Mapping Vineyard Water Status Using Non-Invasive Technologies by a Ground Robot
Juan Fernández‐Novales, Verónica Sáiz-Rubio, Ignacio Barrio, Francisco Rovira-Más, A. Cuenca, Fernando Santos Alves, Joana Valente, Javier Tardáguila, María P. Diago
S43295729. 202146 CitationsOPEN ACCESS
Artificial Intelligence and Novel Sensing Technologies for Assessing Downy Mildew in Grapevine
Inés Hernández, Salvador Gutiérrez, Sara Ceballos, Rubén Íñiguez, Ignacio Barrio, Javier Tardáguila
S2737241975. 202134 CitationsOPEN ACCESS
Impact of Leaf Occlusions on Yield Assessment by Computer Vision in Commercial Vineyards
Rubén Íñiguez, Fernando Palacios, Ignacio Barrio, Inés Hernández, Salvador Gutiérrez, Javier Tardáguila
Agronomy. 202124 CitationsOPEN ACCESS

Related on ScholarIQ

Universidad de La Rioja
Institution
vitisBerry: An Android-smartphone application to early evaluate the number of grapevine berries by means of image analysis
Paper
Deep learning for the differentiation of downy mildew and spider mite in grapevine under field conditions
Paper
Monitoring and Mapping Vineyard Water Status Using Non-Invasive Technologies by a Ground Robot
Paper
Artificial Intelligence and Novel Sensing Technologies for Assessing Downy Mildew in Grapevine
Paper
Impact of Leaf Occlusions on Yield Assessment by Computer Vision in Commercial Vineyards
Paper
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