Jan Platoš

2.3k total citations · 1 hit paper
154 papers, 1.3k citations indexed

About

Jan Platoš is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Jan Platoš has authored 154 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 99 papers in Artificial Intelligence, 31 papers in Computer Vision and Pattern Recognition and 25 papers in Computer Networks and Communications. Recurrent topics in Jan Platoš's work include Evolutionary Algorithms and Applications (32 papers), Metaheuristic Optimization Algorithms Research (29 papers) and Algorithms and Data Compression (18 papers). Jan Platoš is often cited by papers focused on Evolutionary Algorithms and Applications (32 papers), Metaheuristic Optimization Algorithms Research (29 papers) and Algorithms and Data Compression (18 papers). Jan Platoš collaborates with scholars based in Czechia, India and United States. Jan Platoš's co-authors include Václav Snåšel, Pavel Krömer, Siddhartha Bhattacharyya, Aboul Ella Hassanien, Rajib Bag, Surbhi Bhatia, Koyel Chakraborty, Ajith Abraham, Sandip Dey and Stanislav Mišák and has published in prestigious journals such as PLoS ONE, Scientific Reports and IEEE Transactions on Geoscience and Remote Sensing.

In The Last Decade

Jan Platoš

144 papers receiving 1.2k citations

Hit Papers

Sentiment Analysis of COVID-19 tweets by Deep Learning Cl... 2020 2026 2022 2024 2020 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jan Platoš Czechia 17 673 190 175 163 157 154 1.3k
Kamal Jambi Saudi Arabia 15 697 1.0× 137 0.7× 191 1.1× 238 1.5× 200 1.3× 62 1.2k
Waqas Haider Bangyal Pakistan 19 600 0.9× 164 0.9× 114 0.7× 87 0.5× 168 1.1× 51 1.2k
Mohammad‐Reza Feizi‐Derakhshi Iran 20 690 1.0× 294 1.5× 97 0.6× 136 0.8× 255 1.6× 98 1.4k
Andronicus A. Akinyelu South Africa 12 671 1.0× 198 1.0× 109 0.6× 133 0.8× 236 1.5× 25 1.3k
Liang Zhao United States 22 988 1.5× 263 1.4× 163 0.9× 243 1.5× 271 1.7× 192 2.0k
Yuan Tian China 26 700 1.0× 315 1.7× 109 0.6× 268 1.6× 300 1.9× 123 2.0k
Dymitr Ruta United Arab Emirates 16 656 1.0× 324 1.7× 74 0.4× 140 0.9× 244 1.6× 61 1.6k
Mohammad A. Hassonah Jordan 11 635 0.9× 140 0.7× 87 0.5× 193 1.2× 219 1.4× 12 978
Yilin Yan United States 10 635 0.9× 352 1.9× 110 0.6× 129 0.8× 122 0.8× 23 1.3k
Pedro Isasi Spain 19 653 1.0× 274 1.4× 118 0.7× 127 0.8× 100 0.6× 118 1.2k

Countries citing papers authored by Jan Platoš

Since Specialization
Citations

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

Fields of papers citing papers by Jan Platoš

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jan Platoš

This figure shows the co-authorship network connecting the top 25 collaborators of Jan Platoš. A scholar is included among the top collaborators of Jan Platoš 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 Jan Platoš. Jan Platoš 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.
Chakraborty, Pritam, Anjan Bandyopadhyay, Siddhartha Bhattacharyya, & Jan Platoš. (2025). IndiVNet A region adaptive semantic image segmentation for autonomous driving in unstructured environments. Scientific Reports. 16(1). 2468–2468.
2.
Asghar, Ali, Václav Snåšel, & Jan Platoš. (2025). Health-FedNet: A privacy-preserving federated learning framework for scalable and secure healthcare analytics. Results in Engineering. 27. 106484–106484. 4 indexed citations
3.
Mirjalili, Seyedali, et al.. (2025). A comprehensive DEA-based framework for evaluating sustainability and efficiency of vehicle types: Integrating undesirable inputs and social-environmental indicators. Cleaner Engineering and Technology. 27. 100989–100989. 1 indexed citations
4.
Mirjalili, Seyedali, et al.. (2025). A hybrid DEA–fuzzy clustering approach for accurate reference set identification. Machine Learning with Applications. 23. 100818–100818.
5.
Mani, Ashish, et al.. (2025). Evolutionary Algorithm for the Traveling Salesman Problem With Innovative Encoding on Hybrid Quantum-Classical Machines. IEEE Access. 13. 54223–54239. 1 indexed citations
6.
Ma, Quoc-Phu, Sebastián Basterrech, Radim Halama, et al.. (2024). Application of Instrumented Indentation Test and Neural Networks to determine the constitutive model of in-situ austenitic stainless steel components. Archives of Civil and Mechanical Engineering. 24(2). 3 indexed citations
7.
Basterrech, Sebastián, et al.. (2024). A natural gas consumption forecasting system for continual learning scenarios based on Hoeffding trees with change point detection mechanism. Knowledge-Based Systems. 304. 112482–112482. 3 indexed citations
8.
Lee, Suk‐Hwan, et al.. (2023). Deep Reinforcement Learning Tf-Agent-Based Object Tracking With Virtual Autonomous Drone in a Game Engine. IEEE Access. 11. 124129–124138. 4 indexed citations
9.
Platoš, Jan, et al.. (2023). Attention-based Stacked Bidirectional Long Short-term Memory Model for Word Sense Disambiguation. ACM Transactions on Asian and Low-Resource Language Information Processing. 4 indexed citations
10.
Platoš, Jan, et al.. (2022). Automation of cleaning and ensembles for outliers detection in questionnaire data. Expert Systems with Applications. 206. 117809–117809. 6 indexed citations
11.
Platoš, Jan, et al.. (2022). Differential Game-Based Optimal Control of Autonomous Vehicle Convoy. IEEE Transactions on Intelligent Transportation Systems. 24(3). 2903–2919. 16 indexed citations
12.
Krömer, Pavel, et al.. (2021). Behaviour associated with the presence of a school sports ground: Visual information for policy makers. Children and Youth Services Review. 128. 106150–106150. 6 indexed citations
13.
Chakraborty, Koyel, Surbhi Bhatia, Siddhartha Bhattacharyya, et al.. (2020). Sentiment Analysis of COVID-19 tweets by Deep Learning Classifiers—A study to show how popularity is affecting accuracy in social media. Applied Soft Computing. 97. 106754–106754. 255 indexed citations breakdown →
14.
Platoš, Jan, et al.. (2014). Ternary Tree Optimalization for n-gram Indexing. 47–58.
15.
Platoš, Jan, et al.. (2013). Efficient in-memory data structures for n-grams indexing. 48–58. 1 indexed citations
16.
Platoš, Jan, et al.. (2013). A Linguistic Method into Stemming of Arabic for Data Compression.. 119–128. 1 indexed citations
17.
Platoš, Jan, et al.. (2012). The Bayesian Spam Filter with NCD.. 60–68. 4 indexed citations
18.
Prokop, Lukáš, Stanislav Mišák, Václav Snåšel, Pavel Krömer, & Jan Platoš. (2012). PHOTOVOLTAIC POWER PLANT POWER OUTPUT PREDICTION USING FUZZY RULES. PRZEGLĄD ELEKTROTECHNICZNY. 167–177. 1 indexed citations
19.
Snåšel, Václav, et al.. (2010). Evolving Quasigroups by Genetic Algorithms.. 108–117. 5 indexed citations
20.
Krátký, Michal, et al.. (2010). Fast Fibonacci Encoding Algorithm. 41(1). 72–83. 2 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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