Daniel Madroñal

810 total citations
21 papers, 196 citations indexed

About

Daniel Madroñal is a scholar working on Media Technology, Atmospheric Science and Biomedical Engineering. According to data from OpenAlex, Daniel Madroñal has authored 21 papers receiving a total of 196 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Media Technology, 5 papers in Atmospheric Science and 5 papers in Biomedical Engineering. Recurrent topics in Daniel Madroñal's work include Remote-Sensing Image Classification (15 papers), Advanced Chemical Sensor Technologies (5 papers) and Remote Sensing and Land Use (5 papers). Daniel Madroñal is often cited by papers focused on Remote-Sensing Image Classification (15 papers), Advanced Chemical Sensor Technologies (5 papers) and Remote Sensing and Land Use (5 papers). Daniel Madroñal collaborates with scholars based in Spain, Italy and France. Daniel Madroñal's co-authors include C. Sanz, Raquel Lazcano, Eduardo Juárez, Rubén Salvador, Himar Fabelo, Samuel Ortega, Gustavo M. Callicó, Raúl Guerra, Sebastián López and Roberto Sarmiento and has published in prestigious journals such as IEEE Access, Sensors and Remote Sensing.

In The Last Decade

Daniel Madroñal

21 papers receiving 187 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Madroñal Spain 8 71 54 44 35 26 21 196
Raquel Lazcano Spain 8 71 1.0× 53 1.0× 42 1.0× 35 1.0× 25 1.0× 18 191
David Helbert France 9 64 0.9× 17 0.3× 147 3.3× 25 0.7× 14 0.5× 28 249
Worku Jifara China 5 68 1.0× 54 1.0× 132 3.0× 37 1.1× 11 0.4× 7 212
Lingyan Ran China 8 71 1.0× 63 1.2× 152 3.5× 23 0.7× 6 0.2× 26 308
Yinghua Fu China 10 34 0.5× 119 2.2× 151 3.4× 28 0.8× 5 0.2× 27 259
Przemysław Głomb Poland 7 94 1.3× 8 0.1× 54 1.2× 20 0.6× 33 1.3× 25 228
Hrushikesh Garud India 8 165 2.3× 31 0.6× 332 7.5× 24 0.7× 7 0.3× 18 406
P. Sriramakrishnan India 10 13 0.2× 74 1.4× 184 4.2× 26 0.7× 15 0.6× 28 314
Telagarapu Prabhakar India 8 46 0.6× 27 0.5× 72 1.6× 17 0.5× 1 0.0× 30 186
Vanika Singhal India 9 49 0.7× 35 0.6× 146 3.3× 24 0.7× 8 0.3× 19 305

Countries citing papers authored by Daniel Madroñal

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Madroñal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Madroñal

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

All Works

20 of 20 papers shown
1.
Madroñal, Daniel, Francesca Palumbo, Alessandro Capotondi, & Andrea Marongiu. (2021). Unmanned Vehicles in Smart Farming: a Survey and a Glance at Future Horizons. UNICA IRIS Institutional Research Information System (University of Cagliari). 1–8. 11 indexed citations
2.
Lazcano, Raquel, Daniel Madroñal, Raquel León, et al.. (2019). Parallel Implementations Assessment of a Spatial-Spectral Classifier for Hyperspectral Clinical Applications. IEEE Access. 7. 152316–152333. 10 indexed citations
3.
Madroñal, Daniel, Raquel Lazcano, Karol Desnos, et al.. (2019). PAPIFY: Automatic Instrumentation and Monitoring of Dynamic Dataflow Applications Based on PAPI. IEEE Access. 7. 111801–111812. 3 indexed citations
4.
Madroñal, Daniel, et al.. (2019). Run-time performance monitoring of hardware accelerators. 289–291. 2 indexed citations
5.
Florimbi, Giordana, Himar Fabelo, Emanuele Torti, et al.. (2018). Accelerating the K-Nearest Neighbors Filtering Algorithm to Optimize the Real-Time Classification of Human Brain Tumor in Hyperspectral Images. Sensors. 18(7). 2314–2314. 30 indexed citations
6.
Lazcano, Raquel, Daniel Madroñal, Himar Fabelo, et al.. (2018). Adaptation of an Iterative PCA to a Manycore Architecture for Hyperspectral Image Processing. Journal of Signal Processing Systems. 91(7). 759–771. 8 indexed citations
7.
Lazcano, Raquel, José F. López, Daniel Madroñal, et al.. (2018). Implementation of the Principal Component Analysis onto High-Performance Computer Facilities for Hyperspectral Dimensionality Reduction: Results and Comparisons. Remote Sensing. 10(6). 864–864. 32 indexed citations
8.
9.
Ortega, Samuel, Himar Fabelo, Rafael Camacho, et al.. (2017). P03.18 Detection of human brain cancer in pathological slides using hyperspectral images. Neuro-Oncology. 19(suppl_3). iii37–iii37. 3 indexed citations
10.
Salvador, Rubén, Himar Fabelo, Daniel Madroñal, et al.. (2017). High-level design using Intel FPGA OpenCL: A hyperspectral imaging spatial-spectral classifier. Acceda (Universidad de Las Palmas de Gran Canaria). 1. 1–8. 11 indexed citations
11.
Madroñal, Daniel, Raquel Lazcano, Rubén Salvador, et al.. (2017). SVM-based real-time hyperspectral image classifier on a manycore architecture. Journal of Systems Architecture. 80. 30–40. 26 indexed citations
12.
Madroñal, Daniel, Raquel Lazcano, Himar Fabelo, et al.. (2017). Energy consumption characterization of a Massively Parallel Processor Array (MPPA) platform running a hyperspectral SVM classifier. Acceda (Universidad de Las Palmas de Gran Canaria). 1–6. 4 indexed citations
13.
Madroñal, Daniel, Samuel Ortega, Himar Fabelo, et al.. (2017). Parallel exploitation of a spatial-spectral classification approach for hyperspectral images on RVC-CAL. 62. 13–13. 1 indexed citations
14.
Salvador, Rubén, Samuel Ortega, Daniel Madroñal, et al.. (2017). HELICoiD. Acceda (Universidad de Las Palmas de Gran Canaria). 313–318. 5 indexed citations
15.
Lazcano, Raquel, Daniel Madroñal, Himar Fabelo, et al.. (2017). Parallel implementation of an iterative PCA algorithm for hyperspectral images on a manycore platform. Acceda (Universidad de Las Palmas de Gran Canaria). 62. 1–6. 2 indexed citations
16.
Lazcano, Raquel, Daniel Madroñal, Rubén Salvador, et al.. (2017). Porting a PCA-based hyperspectral image dimensionality reduction algorithm for brain cancer detection on a manycore architecture. Journal of Systems Architecture. 77. 101–111. 31 indexed citations
17.
Madroñal, Daniel, Raquel Lazcano, Himar Fabelo, et al.. (2016). Hyperspectral image classification using a parallel implementation of the linear SVM on a Massively Parallel Processor Array (MPPA) platform. Acceda (Universidad de Las Palmas de Gran Canaria). 3. 154–160. 3 indexed citations
18.
Lazcano, Raquel, Daniel Madroñal, Karol Desnos, et al.. (2016). Parallelism exploitation of a PCA algorithm for hyperspectral images using RVC-CAL. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 10007. 100070H–100070H. 2 indexed citations
19.
Madroñal, Daniel, Himar Fabelo, Raquel Lazcano, et al.. (2016). Parallel implementation of a hyperspectral image linear SVM classifier using RVC-CAL. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 10007. 1000709–1000709. 3 indexed citations
20.
Salvador, Rubén, Himar Fabelo, Raquel Lazcano, et al.. (2016). Demo: HELICoiD tool demonstrator for real-time brain cancer detection. Acceda (Universidad de Las Palmas de Gran Canaria). 17. 237–238. 2 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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