Andrés Camero

933 total citations · 1 hit paper
18 papers, 472 citations indexed

About

Andrés Camero is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Media Technology. According to data from OpenAlex, Andrés Camero has authored 18 papers receiving a total of 472 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 4 papers in Media Technology. Recurrent topics in Andrés Camero's work include Remote-Sensing Image Classification (3 papers), Neural Networks and Applications (3 papers) and Machine Learning in Materials Science (2 papers). Andrés Camero is often cited by papers focused on Remote-Sensing Image Classification (3 papers), Neural Networks and Applications (3 papers) and Machine Learning in Materials Science (2 papers). Andrés Camero collaborates with scholars based in Germany, Spain and United States. Andrés Camero's co-authors include Enrique Alba, Xiao Xiang Zhu, Jingliang Hu, Jamal Toutouh, Laura Leal-Taixé, Timothy Davis, Giovanni Marchisio, Daniel Cremers, Çağlar Şenaras and Mark Weber and has published in prestigious journals such as Scientific Reports, IEEE Access and Applied Soft Computing.

In The Last Decade

Andrés Camero

16 papers receiving 454 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.

Smart City and information technology: A review

2019 283 citations Andrés Camero, Enrique Alba Cities profile →

Peers

Andrés Camero

TRANS

CVPR

CNC

Stéphane Cédric Koumetio Tekouabou Morocco

Dimitris Karampatzakis Greece

Uwe Wössner Germany

Fahim Arif Pakistan

Aritz Bilbao-Jayo Spain

Devanjan Bhattacharya India

Fabian Dembski Germany

Ivana Šemanjski Belgium

Yelena Popova Latvia

João Paulo Just Peixoto Brazil

Stéphane Cédric Koumetio Tekouabou Morocco

Andrés Camero

78 ×0.3

87 ×0.9

TRANS

74 ×1.1

22 ×0.4

CVPR

42 ×0.8

CNC

Citations per year, relative to Andrés Camero Andrés Camero (= 1×) peers Stéphane Cédric Koumetio Tekouabou

Countries citing papers authored by Andrés Camero

Since Specialization

Citations

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

Fields of papers citing papers by Andrés Camero

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andrés Camero

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

All Works

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18 of 18 papers shown

Camero, Andrés, et al.. (2026). A deep dive into OpenStreetMap research since its inception (2008–2024): contributors, topics, and future trends. International Journal of Geographical Information Systems. 1–55.

Camero, Andrés, et al.. (2024). DC4Flood: A Deep Clustering Framework for Rapid Flood Detection Using Sentinel-1 SAR Imagery. IEEE Geoscience and Remote Sensing Letters. 21. 1–5. 3 indexed citations

Kreibich, Heidi, et al.. (2024). A satellite imagery-driven framework for rapid resource allocation in flood scenarios to enhance loss and damage fund effectiveness. Scientific Reports. 14(1). 19290–19290. 2 indexed citations

Camero, Andrés, et al.. (2024). An uncertainty-based objective function for hyperparameter optimization in Gaussian processes applied to expensive black-box problems. Applied Soft Computing. 154. 111325–111325. 2 indexed citations

Piraud, Marie, Andrés Camero, Markus Götz, et al.. (2023). Providing AI expertise as an infrastructure in academia. Patterns. 4(8). 100819–100819.

Hu, Jingliang, Rong Liu, Danfeng Hong, et al.. (2023). MDAS: a new multimodal benchmark dataset for remote sensing. Earth system science data. 15(1). 113–131. 40 indexed citations

Weber, Mark, Andrés Camero, Jingliang Hu, et al.. (2022). DynamicEarthNet: Daily Multi-Spectral Satellite Dataset for Semantic Change Segmentation. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 21126–21135. 75 indexed citations

Rußwurm, Marc, Andrés Camero, Grega Milčinski, et al.. (2021). DENETHOR: The DynamicEarthNET dataset for Harmonized, inter-Operable, analysis-Ready, daily crop monitoring from space. elib (German Aerospace Center). 10 indexed citations

Camero, Andrés, et al.. (2021). Compact Neural Architecture Search for Local Climate Zones Classification. elib (German Aerospace Center). 393–398. 1 indexed citations

10.

Camero, Andrés, et al.. (2021). Bayesian neural architecture search using a training-free performance metric. Applied Soft Computing. 106. 107356–107356. 14 indexed citations

11.

Camero, Andrés, Jamal Toutouh, & Enrique Alba. (2020). Random error sampling-based recurrent neural network architecture optimization. Engineering Applications of Artificial Intelligence. 96. 103946–103946. 15 indexed citations

12.

Camero, Andrés, Jamal Toutouh, & Enrique Alba. (2019). A Specialized Evolutionary Strategy Using Mean Absolute Error Random Sampling to Design Recurrent Neural Networks.. arXiv (Cornell University). 3 indexed citations

13.

Camero, Andrés & Enrique Alba. (2019). Smart City and information technology: A review. Cities. 93. 84–94. 283 indexed citations breakdown →

14.

Camero, Andrés, et al.. (2019). JSDoop and TensorFlow.js: Volunteer Distributed Web Browser-Based Neural Network Training. IEEE Access. 7. 158671–158684. 6 indexed citations

15.

Camero, Andrés, Jamal Toutouh, Javier Ferrer, & Enrique Alba. (2019). Waste generation prediction under uncertainty in smart cities through deep neuroevolution. Revista Facultad de Ingeniería Universidad de Antioquia. 128–138. 10 indexed citations

16.

Camero, Andrés, et al.. (2018). Customer Segmentation Based on the Electricity Demand Signature: The Andalusian Case. Energies. 11(7). 1788–1788. 4 indexed citations

17.

Camero, Andrés, et al.. (2018). Road map partitioning for routing by using a micro steady state evolutionary algorithm. Engineering Applications of Artificial Intelligence. 71. 155–165. 3 indexed citations

18.

Camero, Andrés, et al.. (2017). Tile map size optimization for real world routing by using differential evolution. Repositorio Institucional de la Universidad de Málaga (University of Málaga). 4. 1482–1488. 1 indexed citations

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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