Charis Lanaras

1.1k citations
9 papers · 710 · 1 hit paper · h-index 6

Impact in

Papers in

Charis Lanaras

9 papers receiving 689 citations

Charis Lanaras's Hit Papers

Hyperspectral Super-Resolution by Coupled Spectral Unmixing 2015 · 323 citations
3230+3+7Years since publication100200300

Peers

Charis Lanaras
Comparison fields: 5 of 60
  • Media Technology 561
  • Computer Vision and Pattern Recognition 452
  • Ecology 91
  • Atmospheric Science 62
  • Computational Mathematics 2
Replace E. Carmona with:
E. Carmona Germany
Hao Cui China
Rafael Pires de Lima United States
Sara Parrilli Italy
Guoming Gao China
Shuli Cheng China
Yufeng Cheng China
Leonardo Santurri Italy
Zhipeng Dong China
Charis Lanaras relative to E. Carmona Germany E. Carmona's profile →
Citations per field
00.5×4.4×
E. Carmona · 1×
Citations per year

Countries citing papers authored by Charis Lanaras

Since Specialization
Citations

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

Fields of papers citing papers by Charis Lanaras

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 10 scholars most cited alongside Charis Lanaras, 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 Charis Lanaras Line = papers co-authored together Charis Lanaras links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1
Hyperspectral Super-Resolution by Coupled Spectral Unmixing
Hit paper breakdown →
2015323
2 2018244
3 201759
4 201734
5 201833
6 201514
7
Automated detection of lunar rockfalls using a Faster Region-based Convolutional Neural Network
20181
8
Lunar Rockfall Detection and Mapping usinng Deep Neural Networks
20191
9 20191

About Charis Lanaras

Charis Lanaras is a scholar working on Computer Vision and Pattern Recognition, Media Technology, Astronomy and Astrophysics, Artificial Intelligence and Aerospace Engineering, having authored 9 papers that have together received 710 indexed citations. Recurring topics across this work include Advanced Image Fusion Techniques (5 papers), Remote-Sensing Image Classification (4 papers), Image Processing and 3D Reconstruction (3 papers), Image and Signal Denoising Methods (3 papers), Planetary Science and Exploration (3 papers), Advanced Image Processing Techniques (2 papers), Computational Physics and Python Applications (1 paper) and Seismology and Earthquake Studies (1 paper). The work is most often cited by research in Media Technology (561 citations), Computer Vision and Pattern Recognition (452 citations), Ecology (91 citations), Atmospheric Science (62 citations) and Computational Mathematics (2 citations). Charis Lanaras has collaborated with scholars based in Switzerland, Portugal and Germany. Frequent co-authors include Konrad Schindler, E. Baltsavias, José M. Bioucas‐Dias, Silvano Galliani, U. Mall, Andrea Manconi, Simon Loew, Valentin Bickel, Emmanuel P. Baltsavias and Andrea Manconi. Their work appears in journals such as Remote Sensing, IEEE Transactions on Geoscience and Remote Sensing, ISPRS Journal of Photogrammetry and Remote Sensing, SHILAP Revista de lepidopterología and Repository for Publications and Research Data (ETH Zurich).

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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