Pol Moreno

483 citations
7 papers · 242 · h-index 6

Impact in

Papers in

Pol Moreno

7 papers receiving 230 citations

Peers

Pol Moreno
Comparison fields: 5 of 35
  • Computer Vision and Pattern Recognition 211
  • Computer Graphics and Computer-Aided Design 13
  • Media Technology 26
  • Artificial Intelligence 76
  • Signal Processing 22
Replace Dong Huk Park with:
Dong Huk Park United States
Aron Yu United States
Bor-Chun Chen Taiwan
Tianyu Ding United States
Ziqi Huang Singapore
Haneol Jang South Korea
Gihyun Kwon South Korea
Haibo Chen China
Mahyar Najibi United States
Pol Moreno relative to Dong Huk Park United States Dong Huk Park's profile →
Citations per field
00.5×1.5×2.4×
Dong Huk Park · 1×
Citations per year

Countries citing papers authored by Pol Moreno

Since Specialization
Citations

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

Fields of papers citing papers by Pol Moreno

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Pol Moreno, 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 Pol Moreno Line = papers co-authored together Pol Moreno links everyone, so they are left out of the graph.

All Works

7 of 7 papers shown
#Work
1 2007188
2
NeRF-VAE: A Geometry Aware 3D Scene Generative Model
202119
3 202210
4 20169
5 20178
6
Can we determine the semantics of collocations without using semantics
20135
7 20133

About Pol Moreno

Pol Moreno is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Language and Linguistics, Automotive Engineering and Atomic and Molecular Physics, and Optics, having authored 7 papers that have together received 242 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (2 papers), linguistics and terminology studies (2 papers), Advanced Vision and Imaging (2 papers), Lexicography and Language Studies (1 paper), Time Series Analysis and Forecasting (1 paper), Image Processing Techniques and Applications (1 paper), Image and Object Detection Techniques (1 paper) and Multimodal Machine Learning Applications (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (211 citations), Computer Graphics and Computer-Aided Design (13 citations), Media Technology (26 citations), Artificial Intelligence (76 citations) and Signal Processing (22 citations). Pol Moreno has collaborated with scholars based in United Kingdom, United States and Australia. Frequent co-authors include Nuno Vasconcelos, Leo Wanner, Gabriela Ferraro, Rosalia Schneider, Danilo Jimenez Rezende, Adam R. Kosiorek, Daniel Zoran, Heiko Strathmann, Łukasz Romaszko and Christopher K. I. Williams. Their work appears in journals such as Scientific Reports, IEEE Transactions on Multimedia, International Journal of Lexicography, Edinburgh Research Explorer and Dialnet (Universidad de la Rioja).

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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