Lukáš Picek

472 citations
21 papers · 157 · h-index 8

Impact in

Papers in

    • Venomous Animal Envenomation and Studies 3
    • Smart Agriculture and AI 3
    • Mycorrhizal Fungi and Plant Interactions 2

Lukáš Picek

14 papers receiving 148 citations

Peers

Lukáš Picek
Comparison fields: 5 of 57
  • Ecological Modeling 22
  • Biophysics 17
  • Virology 9
  • Analytical Chemistry 18
  • Plant Science 53
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Citations per year

Countries citing papers authored by Lukáš Picek

Since Specialization
Citations

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

Fields of papers citing papers by Lukáš Picek

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202234
2 202225
3 202215
4 202015
5 202214
6 202412
7
Overview of SnakeCLEF 2021: Automatic Snake Species Identification with Country-Level Focus.
20219
8 20249
9
Plant Recognition by Inception Networks with Test-time Class Prior Estimation.
20186
10
Recognition of the Amazonian flora by Inception Networks with Test-time Class Prior Estimation
20195
11
Coral Reef Annotation, Localisation and Pixel-wise Classification using Mask-RCNN and Bag of Tricks.
20204
12
Overview of the SnakeCLEF 2020: AutomaticSnake Species Identification Challenge.
20203
13 20223
14 20252
15
Sketch2Code: Automatic hand-drawn UI Elements Detection with Faster-RCNN.
20201
16 20250
17
A Deep Learning Method for Visual Recognition of Snake Species.
20210
18 20240
19 20250
20 20250

About Lukáš Picek

Lukáš Picek is a scholar working on Genetics, Plant Science, Ecological Modeling, Molecular Biology and Computer Vision and Pattern Recognition, having authored 21 papers that have together received 157 indexed citations. Recurring topics across this work include Species Distribution and Climate Change (4 papers), Amphibian and Reptile Biology (3 papers), Plant Pathogens and Fungal Diseases (3 papers), Venomous Animal Envenomation and Studies (3 papers), Smart Agriculture and AI (3 papers), Wildlife Ecology and Conservation (2 papers), Spectroscopy and Chemometric Analyses (2 papers) and Mycorrhizal Fungi and Plant Interactions (2 papers). The work is most often cited by research in Ecological Modeling (22 citations), Biophysics (17 citations), Virology (9 citations), Analytical Chemistry (18 citations) and Plant Science (53 citations). Lukáš Picek has collaborated with scholars based in Czechia, United Kingdom and France. Frequent co-authors include Jiřı́ Matas, Milan Šulc, Jacob Heilmann‐Clausen, Thomas Stjernegaard Jeppesen, Isabelle Bolon, Andrew M. Durso, Yash Patel, Kostas Papafitsoros, Lukáš Adam and François Chappuis. Their work appears in journals such as Frontiers in Plant Science, PLoS neglected tropical diseases, Sensors, Field Mycology and 2022 IEEE International Conference on Image Processing (ICIP).

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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