Eduardo Juárez

1.5k total citations
79 papers, 551 citations indexed

About

Eduardo Juárez is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Media Technology. According to data from OpenAlex, Eduardo Juárez has authored 79 papers receiving a total of 551 indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Computer Vision and Pattern Recognition, 26 papers in Signal Processing and 21 papers in Media Technology. Recurrent topics in Eduardo Juárez's work include Video Coding and Compression Technologies (26 papers), Remote-Sensing Image Classification (20 papers) and Advanced Data Compression Techniques (17 papers). Eduardo Juárez is often cited by papers focused on Video Coding and Compression Technologies (26 papers), Remote-Sensing Image Classification (20 papers) and Advanced Data Compression Techniques (17 papers). Eduardo Juárez collaborates with scholars based in Spain, France and Belgium. Eduardo Juárez's co-authors include C. Sanz, Fernando Pescador, M.J. Garrido, Miguel Chavarrías, Rubén Salvador, Daniel Madroñal, Raquel Lazcano, Samuel Ortega, Himar Fabelo and Gustavo M. Callicó and has published in prestigious journals such as IEEE Access, Sensors and Remote Sensing.

In The Last Decade

Eduardo Juárez

74 papers receiving 534 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Eduardo Juárez Spain 12 237 165 102 97 96 79 551
C. Sanz Spain 13 303 1.3× 241 1.5× 99 1.0× 90 0.9× 93 1.0× 77 596
Rubén Salvador Spain 12 103 0.4× 37 0.2× 55 0.5× 73 0.8× 81 0.8× 45 454
S. Ramachandran India 15 454 1.9× 191 1.2× 16 0.2× 18 0.2× 86 0.9× 79 683
Xiaogang Du China 13 230 1.0× 6 0.0× 67 0.7× 91 0.9× 98 1.0× 35 497
Muzammal Naseer United Arab Emirates 13 398 1.7× 71 0.4× 17 0.2× 13 0.1× 88 0.9× 36 702
Roberto Rigamonti Switzerland 8 413 1.7× 40 0.2× 102 1.0× 5 0.1× 54 0.6× 10 548
Philipp Benz South Korea 11 252 1.1× 44 0.3× 22 0.2× 12 0.1× 23 0.2× 12 447

Countries citing papers authored by Eduardo Juárez

Since Specialization
Citations

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

Fields of papers citing papers by Eduardo Juárez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eduardo Juárez

This figure shows the co-authorship network connecting the top 25 collaborators of Eduardo Juárez. A scholar is included among the top collaborators of Eduardo Juárez 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 Eduardo Juárez. Eduardo Juárez 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.
Castaño‐León, Ana M., Elena Salvador Álvarez, Ana Ramos, et al.. (2025). Comprehensive predictive modeling in subarachnoid hemorrhage: integrating radiomics and clinical variables. Neurosurgical Review. 48(1). 528–528.
2.
León, Raquel, Himar Fabelo, Samuel Ortega, et al.. (2025). Unifying heterogeneous hyperspectral databases for in vivo human brain cancer classification: Towards robust algorithm development. Acceda (Universidad de Las Palmas de Gran Canaria). 7. 100183–100183. 2 indexed citations
3.
Chavarrías, Miguel, et al.. (2025). Benchmarking commercial depth sensors for intraoperative markerless registration in neurosurgery applications. International Journal of Computer Assisted Radiology and Surgery. 20(8). 1759–1769.
4.
Lafruit, Gauthier, et al.. (2024). DA4NeRF: Depth-aware Augmentation technique for Neural Radiance Fields. Journal of Visual Communication and Image Representation. 107. 104365–104365.
5.
Chavarrías, Miguel, et al.. (2024). HyperMRI: hyperspectral and magnetic resonance fusion methodology for neurosurgery applications. International Journal of Computer Assisted Radiology and Surgery. 19(7). 1367–1374. 5 indexed citations
6.
Lagares, Alfonso, et al.. (2024). Spectral analysis comparison of pushbroom and snapshot hyperspectral cameras for in vivo brain tissues and chromophore identification. Journal of Biomedical Optics. 29(9). 93510–93510. 2 indexed citations
7.
Pérez‐Núñez, Ángel, Luis Jiménez‐Roldán, Alfonso Lagares, et al.. (2023). Sparse to Dense Ground Truth Pre-Processing in Hyperspectral Imaging for In-Vivo Brain Tumour Detection. 15. 272–277. 2 indexed citations
8.
Chavarrías, Miguel, et al.. (2022). Hyperparameter Optimization for Brain Tumor Classification with Hyperspectral Images. 835–842. 6 indexed citations
9.
Jiménez‐Roldán, Luis, Ángel Pérez‐Núñez, Alfonso Lagares, et al.. (2022). Exploration of Realtime Brain tumor classification from Hyperspectral Images in Heterogeneous Embedded MPSoC. 1–6. 2 indexed citations
10.
Jiménez‐Roldán, Luis, et al.. (2021). Supervised Machine Learning Methods and Hyperspectral Imaging Techniques Jointly Applied for Brain Cancer Classification. Sensors. 21(11). 3827–3827. 57 indexed citations
11.
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
12.
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
13.
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
14.
Juárez, Eduardo. (2016). Session 1: HEVC in embedded systems. 1–1. 1 indexed citations
15.
16.
Juárez, Eduardo, et al.. (2013). System-level PMC-driven energy estimation models in RVC-CAL video codec specifications. 55–62. 2 indexed citations
17.
Juárez, Eduardo, et al.. (2013). A PMC-driven methodology for energy estimation in RVC-CAL video codec specifications. Signal Processing Image Communication. 28(10). 1303–1314. 11 indexed citations
18.
Juárez, Eduardo, et al.. (2011). A DSP based H.264/SVCdecoder for a multimedia terminal. IEEE Transactions on Consumer Electronics. 57(2). 705–712. 5 indexed citations
19.
Pescador, Fernando, et al.. (2007). A real-time H.264 MP decoder based on a DM642 DSP. 1248–1251. 4 indexed citations
20.
Juárez, Eduardo, Marco Mattavelli, & D. Mlynek. (2000). A system-on-a-chip for MPEG-4 multimedia stream processing and communication. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 690–693 vol.3. 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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