Artzai Picón

3.9k total citations · 4 hit papers
61 papers, 2.8k citations indexed

About

Artzai Picón is a scholar working on Artificial Intelligence, Plant Science and Biomedical Engineering. According to data from OpenAlex, Artzai Picón has authored 61 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 12 papers in Plant Science and 11 papers in Biomedical Engineering. Recurrent topics in Artzai Picón's work include Smart Agriculture and AI (12 papers), AI in cancer detection (10 papers) and Spectroscopy and Chemometric Analyses (10 papers). Artzai Picón is often cited by papers focused on Smart Agriculture and AI (12 papers), AI in cancer detection (10 papers) and Spectroscopy and Chemometric Analyses (10 papers). Artzai Picón collaborates with scholars based in Spain, United Kingdom and United States. Artzai Picón's co-authors include Aitor Álvarez-Gila, Adrián Galdrán, David Pardo, Jone Echazarra, Amaia Ortiz‐Barredo, Arantza Bereciartúa-Pérez, Unai Irusta, Alfonso Medela, Sergio Rodríguez-Vaamonde and Ana María Díez-Navajas and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Electrochimica Acta.

In The Last Decade

Artzai Picón

58 papers receiving 2.7k citations

Hit Papers

align trajectories

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.

Automatic Red-Channel underwater image restoration

2014 725 citations Adrián Galdrán, Artzai Picón et al. profile →
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 →
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 →
Few-Shot Learning approach for plant disease classification using images taken in the field

2020 248 citations Artzai Picón, Unai Irusta 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						Papers	Cites
Artzai Picón Spain	21	1.1k	928	460	429	281	61	2.8k
Adel Hafiane France	22	892 0.8×	456 0.5×	232 0.5×	138 0.3×	240 0.9×	70	1.9k
Sotirios A. Tsaftaris United Kingdom	28	1.0k 0.9×	915 1.0×	154 0.3×	119 0.3×	735 2.6×	138	3.3k
S. Arivazhagan India	18	277 0.2×	1.1k 1.1×	213 0.5×	495 1.2×	240 0.9×	143	2.0k
Erchan Aptoula Türkiye	19	530 0.5×	656 0.7×	240 0.5×	652 1.5×	184 0.7×	74	1.7k
Hao Lü China	28	1.1k 1.0×	1.1k 1.2×	380 0.8×	247 0.6×	497 1.8×	101	2.6k
Zhaobin Wang China	23	223 0.2×	941 1.0×	107 0.2×	829 1.9×	236 0.8×	66	2.0k
Tardi Tjahjadi United Kingdom	25	193 0.2×	1.5k 1.6×	67 0.1×	454 1.1×	214 0.8×	96	2.3k
Weidong Zhang China	31	189 0.2×	2.4k 2.6×	163 0.4×	1.1k 2.5×	290 1.0×	123	3.2k
Khurram Khurshid Pakistan	18	111 0.1×	950 1.0×	178 0.4×	611 1.4×	450 1.6×	87	2.0k
Bo Zhao China	23	335 0.3×	956 1.0×	98 0.2×	83 0.2×	398 1.4×	93	1.9k

Countries citing papers authored by Artzai Picón

Since Specialization

Citations

This map shows the geographic impact of Artzai Picón'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 Artzai Picón with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Artzai Picón more than expected).

Fields of papers citing papers by Artzai Picón

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Artzai Picón. 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 Artzai Picón. The network helps show where Artzai Picón may publish in the future.

Co-authorship network of co-authors of Artzai Picón

This figure shows the co-authorship network connecting the top 25 collaborators of Artzai Picón. A scholar is included among the top collaborators of Artzai Picón 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 Artzai Picón. Artzai Picón is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Gajjala, Rajendra Kumar Reddy, E. Fernández, Jean‐Yves Hihn, et al.. (2025). Image-based analysis of electrochromic materials: Gamma correction with a LEGO luminance checker. Electrochimica Acta. 525. 146062–146062. 1 indexed citations

Picón, Artzai, et al.. (2025). Crop-conditional semantic segmentation for efficient agricultural disease assessment. Artificial Intelligence in Agriculture. 15(1). 79–87. 3 indexed citations

Bereciartúa-Pérez, Arantza, et al.. (2024). Deep learning-based instance segmentation for improved pepper phenotyping. SHILAP Revista de lepidopterología. 9. 100555–100555.

Picón, Artzai, et al.. (2024). When synthetic plants get sick: Disease graded image datasets by novel regression-conditional diffusion models. Computers and Electronics in Agriculture. 229. 109690–109690. 4 indexed citations

Picón, Artzai, et al.. (2024). On the analysis of adapting deep learning methods to hyperspectral imaging. Use case for WEEE recycling and dataset. Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy. 330. 125665–125665. 1 indexed citations

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

Sánchez‐Peralta, Luisa F., Ben Glover, Cristina L. Saratxaga, et al.. (2023). Clinical Validation Benchmark Dataset and Expert Performance Baseline for Colorectal Polyp Localization Methods. Journal of Imaging. 9(9). 167–167. 1 indexed citations

Picón, Artzai, Luisa F. Sánchez‐Peralta, Sara Mattana, et al.. (2022). Novel Pixelwise Co-Registered Hematoxylin-Eosin and Multiphoton Microscopy Image Dataset for Human Colon Lesion Diagnosis. Journal of Pathology Informatics. 13. 100012–100012. 7 indexed citations

Picón, Artzai, et al.. (2022). Analysis of Few-Shot Techniques for Fungal Plant Disease Classification and Evaluation of Clustering Capabilities Over Real Datasets. Frontiers in Plant Science. 13. 813237–813237. 27 indexed citations

10.

Picón, Artzai, Alfonso Medela, Luisa F. Sánchez‐Peralta, et al.. (2021). Autofluorescence Image Reconstruction and Virtual Staining for In-Vivo Optical Biopsying. IEEE Access. 9. 32081–32093. 15 indexed citations

11.

Saratxaga, Cristina L., et al.. (2021). Analysis on the Characterization of Multiphoton Microscopy Images for Malignant Neoplastic Colon Lesion Detection under Deep Learning Methods. Journal of Pathology Informatics. 12(1). 27–27. 12 indexed citations

12.

Sánchez‐Peralta, Luisa F., et al.. (2020). Unravelling the effect of data augmentation transformations in polyp segmentation. International Journal of Computer Assisted Radiology and Surgery. 15(12). 1975–1988. 28 indexed citations

13.

Sánchez‐Peralta, Luisa F., et al.. (2020). Eigenloss: Combined PCA-Based Loss Function for Polyp Segmentation. Mathematics. 8(8). 1316–1316. 9 indexed citations

14.

Sánchez‐Peralta, Luisa F., J. Blas Pagador, Artzai Picón, et al.. (2020). PICCOLO White-Light and Narrow-Band Imaging Colonoscopic Dataset: A Performance Comparative of Models and Datasets. Applied Sciences. 10(23). 8501–8501. 56 indexed citations

15.

Sánchez‐Peralta, Luisa F., et al.. (2020). Deep learning to find colorectal polyps in colonoscopy: A systematic literature review. Artificial Intelligence in Medicine. 108. 101923–101923. 119 indexed citations

16.

Medela, Alfonso & Artzai Picón. (2020). Constellation Loss: Improving the Efficiency of Deep Metric Learning Loss Functions for the Optimal Embedding of histopathological images. Journal of Pathology Informatics. 11(1). 38–38. 20 indexed citations

17.

Bereciartúa-Pérez, Arantza, et al.. (2016). 3D active surfaces for liver segmentation in multisequence MRI images. Computer Methods and Programs in Biomedicine. 132. 149–160. 11 indexed citations

18.

Ballesteros-Peña, Sendoa, et al.. (2015). Influencia del esmalte de uñas en los valores de saturación de oxígeno en pacientes sometidos a pulsioximetría: una revisión sistemática. Emergencias. 27(5). 325–331. 3 indexed citations

19.

Picón, Artzai, et al.. (2007). USO DE UN INOCULANTE TERMOFILICO EN LA TRANSFORMACIÓN DE RESIDUOS SÓLIDOS URBANOS (RSU). SHILAP Revista de lepidopterología.

20.

Bereciartúa-Pérez, Arantza, et al.. (2004). Surface inspection of polyurethane foam by image processing and artificial neural networks techniques. International Conference on Signal Processing. 30(7). 9–1012.

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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