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Inés Hernández
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2020 – today
- 2024
- [j4]Rubén Íñiguez, Salvador Gutiérrez, Carlos Poblete-Echeverría, Inés Hernández, Ignacio Barrio, Javier Tardáguila:
Deep learning modelling for non-invasive grape bunch detection under diverse occlusion conditions. Comput. Electron. Agric. 226: 109421 (2024) - [j3]Inés Hernández, Salvador Gutiérrez, Ignacio Barrio, Rubén Íñiguez, Javier Tardáguila:
In-field disease symptom detection and localisation using explainable deep learning: Use case for downy mildew in grapevine. Comput. Electron. Agric. 226: 109478 (2024) - [i1]David Herrera-Poyatos, Jacinto Domínguez-Rull, Rosana Montes, Inés Hernández, Ignacio Barrio, Carlos Poblete-Echeverría, Javier Tardáguila, Francisco Herrera, Andrés Herrera-Poyatos:
Small data deep learning methodology for in-field disease detection. CoRR abs/2409.17119 (2024) - 2021
- [j2]Salvador Gutiérrez, Inés Hernández, Sara Ceballos, Ignacio Barrio, Ana Díez Navajas, Javier Tardáguila:
Deep learning for the differentiation of downy mildew and spider mite in grapevine under field conditions. Comput. Electron. Agric. 182: 105991 (2021) - 2020
- [j1]Fernando Palacios, Gloria Bueno, Jesús Salido, María-Paz Diago, Inés Hernández, Javier Tardáguila:
Automated grapevine flower detection and quantification method based on computer vision and deep learning from on-the-go imaging using a mobile sensing platform under field conditions. Comput. Electron. Agric. 178: 105796 (2020)
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last updated on 2024-10-31 20:12 CET by the dblp team
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