Jan Hůla

432 citations
12 papers · 174 · h-index 4

Impact in

Papers in

Jan Hůla

10 papers receiving 167 citations

Peers

Jan Hůla
Comparison fields: 5 of 72
  • Computer Vision and Pattern Recognition 82
  • Media Technology 16
  • Industrial and Manufacturing Engineering 16
  • Health Informatics 2
  • Artificial Intelligence 47
Replace Aadarsh Jha with:
Aadarsh Jha United States
Shao-Yuan Lo United States
R. Vijaya Kumar Reddy India
Edmundo Casas Spain
Marek Vajgl Czechia
Ziteng Gao China
Khurram Azeem Hashmi Germany
Lemeng Wu United States
Jan Hůla relative to Aadarsh Jha United States Aadarsh Jha's profile →
Citations per field
00.5×1.5×
Aadarsh Jha · 1×
Citations per year

Countries citing papers authored by Jan Hůla

Since Specialization
Citations

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

Fields of papers citing papers by Jan Hůla

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 21 scholars most cited alongside Jan Hůla, 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 Jan Hůla Line = papers co-authored together Jan Hůla links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1 202299
2 202033
3 202217
4
Looking for ELMo's friends: Sentence-Level Pretraining Beyond Language Modeling.
201811
5 20183
6 20213
7 20242
8 20182
9 20242
10 20202
11 20250
12 20240

About Jan Hůla

Jan Hůla is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Industrial and Manufacturing Engineering, Computer Networks and Communications and Information Systems, having authored 12 papers that have together received 174 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (4 papers), Image Enhancement Techniques (2 papers), Authorship Attribution and Profiling (2 papers), Scheduling and Optimization Algorithms (2 papers), Advanced Neural Network Applications (2 papers), Consumer Market Behavior and Pricing (1 paper), Multimodal Machine Learning Applications (1 paper) and Language and cultural evolution (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (82 citations), Media Technology (16 citations), Industrial and Manufacturing Engineering (16 citations), Health Informatics (2 citations) and Artificial Intelligence (47 citations). Jan Hůla has collaborated with scholars based in Czechia, China and Estonia. Frequent co-authors include Petr Hurtík, Marek Vajgl, Stefania Tomasiello, Mikoláš Janota, Édouard Grave, Berlin Chen, Patrick Xia, Přemysl Šůcha, Raghavendra Pappagari and Najoung Kim. Their work appears in journals such as Neural Computing and Applications, IEEE Transactions on Fuzzy Systems, Computers & Operations Research, Journal of Quantitative Linguistics and Corpus Linguistics and Linguistic Theory.

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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