Daniel Vaquero

725 citations
29 papers · 444 indexed · h-index 9

Impact in

    • Advanced Image and Video Retrieval Techniques
    • Advanced Vision and Imaging
    • Video Surveillance and Tracking Methods
    • Visual Attention and Saliency Detection
    • Human Pose and Action Recognition
    • Face recognition and analysis
    • Advanced Neural Network Applications
    • Image Processing Techniques and Applications

Papers in

Daniel Vaquero

25 papers receiving 426 citations

Peers

Daniel Vaquero
Comparison fields: 5 of 54
  • Computer Vision and Pattern Recognition 338
  • Media Technology 58
  • Computer Graphics and Computer-Aided Design 21
  • Hardware and Architecture 19
  • Instrumentation 7
Replace Dikpal Reddy with:
Dikpal Reddy United States
Mark E. Lasher United States
Taeg Sang Cho United States
Mingzhao He China
Yoshito Tsunoda Japan
César O. Torres Colombia
Lukas Gruber Austria
Peiqi Duan China
Tsung-Han Tsai Taiwan
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Citations per field
00.5×4.4×
Dikpal Reddy · 1×
Citations per year

Countries citing papers authored by Daniel Vaquero

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Vaquero

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Daniel Vaquero, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel Vaquero Line = papers co-authored together Daniel Vaquero links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
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An entropy minimization approach for designing W-operators.
20071
20 20057

About Daniel Vaquero

Daniel Vaquero is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition, Materials Chemistry, Media Technology and Atomic and Molecular Physics, and Optics, having authored 29 papers that have together received 444 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (10 papers), Advanced Image and Video Retrieval Techniques (9 papers), 2D Materials and Applications (7 papers), Graphene research and applications (5 papers), Visual Attention and Saliency Detection (5 papers), Computer Graphics and Visualization Techniques (4 papers), Perovskite Materials and Applications (4 papers) and Semiconductor Quantum Structures and Devices (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (338 citations), Media Technology (58 citations), Computer Graphics and Computer-Aided Design (21 citations), Hardware and Architecture (19 citations) and Instrumentation (7 citations). Daniel Vaquero has collaborated with scholars based in United States, Spain and Netherlands. Frequent co-authors include Rogério Feris, Natasha Gelfand, Kari Pulli, Marius Tico, Lisa M. Brown, Duan Tran, Matthew Turk, Arun Hampapur, Matthew Turk and Marc Levoy. Their work appears in journals such as 2D Materials, ACM Transactions on Graphics, ACS Photonics, Nature Communications and Energy & environment materials.

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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