Jone Echazarra

1.2k total citations · 2 hit papers
8 papers, 851 citations indexed

About

Jone Echazarra is a scholar working on Plant Science, Analytical Chemistry and Molecular Biology. According to data from OpenAlex, Jone Echazarra has authored 8 papers receiving a total of 851 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Plant Science, 2 papers in Analytical Chemistry and 1 paper in Molecular Biology. Recurrent topics in Jone Echazarra's work include Smart Agriculture and AI (7 papers), Spectroscopy and Chemometric Analyses (2 papers) and Plant Disease Management Techniques (2 papers). Jone Echazarra is often cited by papers focused on Smart Agriculture and AI (7 papers), Spectroscopy and Chemometric Analyses (2 papers) and Plant Disease Management Techniques (2 papers). Jone Echazarra collaborates with scholars based in Spain and Germany. Jone Echazarra's co-authors include Artzai Picón, Aitor Álvarez-Gila, Amaia Ortiz‐Barredo, Sergio Rodríguez-Vaamonde, Ana María Díez-Navajas, Unai Irusta, Arantza Bereciartúa-Pérez, Christian Klukas, Jeroen Baert and Alberto Serrano and has published in prestigious journals such as SHILAP Revista de lepidopterología, Computers and Electronics in Agriculture and Applied Sciences.

In The Last Decade

Jone Echazarra

7 papers receiving 823 citations

Hit Papers

Deep convolutional neural networks for mobile capture dev... 2017 2026 2020 2023 2018 2017 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Deep convolutional neural networks for mobile capture device-based crop disease classification in the wild
    2018 367 citations Artzai Picón, Aitor Álvarez-Gila et al. Computers and Electronics in Agriculture profile →
  2. Automatic plant disease diagnosis using mobile capture devices, applied on a wheat use case
    2017 300 citations Artzai Picón, Aitor Álvarez-Gila et al. Computers and Electronics in Agriculture profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jone Echazarra Spain 5 774 331 173 49 33 8 851
V. K. Singh India 10 1.1k 1.4× 446 1.3× 186 1.1× 54 1.1× 67 2.0× 43 1.2k
Sue Han Lee Malaysia 7 727 0.9× 295 0.9× 178 1.0× 34 0.7× 66 2.0× 15 860
Edna C. Too Kenya 5 756 1.0× 290 0.9× 168 1.0× 27 0.6× 65 2.0× 11 922
Mónica G. Larese Argentina 6 664 0.9× 251 0.8× 192 1.1× 28 0.6× 96 2.9× 12 808
Keming Du China 10 669 0.9× 270 0.8× 188 1.1× 42 0.9× 40 1.2× 15 772
J. Arun Pandian India 9 772 1.0× 280 0.8× 115 0.7× 46 0.9× 54 1.6× 32 917
Nalini Kanta Barpanda India 7 611 0.8× 300 0.9× 59 0.3× 30 0.6× 31 0.9× 29 728
Koushik Nagasubramanian United States 8 540 0.7× 225 0.7× 209 1.2× 37 0.8× 12 0.4× 10 674
Aanis Ahmad United States 7 503 0.6× 150 0.5× 101 0.6× 34 0.7× 14 0.4× 12 553
Pascal Welke Germany 5 324 0.4× 224 0.7× 287 1.7× 49 1.0× 17 0.5× 16 542

Countries citing papers authored by Jone Echazarra

Since Specialization
Citations

This map shows the geographic impact of Jone Echazarra's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jone Echazarra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jone Echazarra more than expected).

Fields of papers citing papers by Jone Echazarra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jone Echazarra. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jone Echazarra. The network helps show where Jone Echazarra may publish in the future.

Co-authorship network of co-authors of Jone Echazarra

This figure shows the co-authorship network connecting the top 25 collaborators of Jone Echazarra. A scholar is included among the top collaborators of Jone Echazarra based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jone Echazarra. Jone Echazarra is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

8 of 8 papers shown
1.
Bereciartúa-Pérez, Arantza, et al.. (2024). Deep learning-based instance segmentation for improved pepper phenotyping. SHILAP Revista de lepidopterología. 9. 100555–100555.
2.
Bereciartúa-Pérez, Arantza, et al.. (2024). Estimation of flea beetle damage in the field using a multistage deep learning-based solution. Artificial Intelligence in Agriculture. 13. 18–31. 1 indexed citations
3.
Bereciartúa-Pérez, Arantza, et al.. (2023). Damage assessment of soybean and redroot amaranth plants in greenhouse through biomass estimation and deep learning-based symptom classification. SHILAP Revista de lepidopterología. 5. 100243–100243. 9 indexed citations
4.
Bereciartúa-Pérez, Arantza, et al.. (2022). Deep Learning-Based Method for Accurate Real-Time Seed Detection in Glass Bottle Manufacturing. Applied Sciences. 12(21). 11192–11192. 2 indexed citations
5.
Picón, Artzai, Aitor Álvarez-Gila, Unai Irusta, & Jone Echazarra. (2020). WHY DEEP LEARNING PERFORMS BETTER THAN CLASSICAL MACHINE LEARNING?. DYNA. 95(1). 119–122. 20 indexed citations
6.
Picón, Artzai, et al.. (2019). Crop conditional Convolutional Neural Networks for massive multi-crop plant disease classification over cell phone acquired images taken on real field conditions. Computers and Electronics in Agriculture. 167. 105093–105093. 152 indexed citations
7.
Picón, Artzai, et al.. (2018). Deep convolutional neural networks for mobile capture device-based crop disease classification in the wild. Computers and Electronics in Agriculture. 161. 280–290. 367 indexed citations breakdown →
8.
Picón, Artzai, Aitor Álvarez-Gila, Jone Echazarra, et al.. (2017). Automatic plant disease diagnosis using mobile capture devices, applied on a wheat use case. Computers and Electronics in Agriculture. 138. 200–209. 300 indexed citations breakdown →

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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