Andrey Filchenkov
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Information Systems top 10%
- Computer Networks and Communications
- Industrial and Manufacturing Engineering
- Co-authors
- Aleksandr FarseevTat‐Seng ChuaAnatoly ShalytoValeriy VyatkinEvgeny PutinLidia PivovarovaI. S. LobanovKirill Kochetov
- Topics
- Machine Learning and Data Classification (9 papers)Machine Learning and Algorithms (5 papers)Generative Adversarial Networks and Image Synthesis (4 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE AccessFuture Generation Computer Systems
In The Last Decade
Andrey Filchenkov
56 papers receiving 349 citations
Peers
Comparison fields: 5 of 94
- Artificial Intelligence 147
- Computer Vision and Pattern Recognition 82
- Information Systems 81
- Computer Networks and Communications 43
- Industrial and Manufacturing Engineering 22
Countries citing papers authored by Andrey Filchenkov
This map shows the geographic impact of Andrey Filchenkov'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 Andrey Filchenkov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrey Filchenkov more than expected).
Fields of papers citing papers by Andrey Filchenkov
This network shows the impact of papers produced by Andrey Filchenkov. 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 Andrey Filchenkov. The network helps show where Andrey Filchenkov may publish in the future.
Co-authorship network of co-authors of Andrey Filchenkov
This figure shows the co-authorship network connecting the top 25 collaborators of Andrey Filchenkov. A scholar is included among the top collaborators of Andrey Filchenkov 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 Andrey Filchenkov. Andrey Filchenkov is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 8 | |
| 3 | 1 | |
| 4 | 18 | |
| 5 | 3 | |
| 6 | 5 | |
| 7 | 1 | |
| 8 | 4 | |
| 9 | 3 | |
| 10 | 3 | |
| 11 | Linear Distillation Learning. | 1 |
| 12 | 1 | |
| 13 | 1 | |
| 14 | 11 | |
| 15 | RICH-CPL: Fact Extraction from Wikipedia-sized Corpora for Morphologically Rich Languages | 0 |
| 16 | Pollen grain recognition using convolutional neural network. | 23 |
| 17 | Meta-learning System for Automated Clustering. | 4 |
| 18 | NDSE: Instance Generation for Classification by Given Meta-Feature Description. | 1 |
| 19 | Towards cluster validity index evaluation and selection | 7 |
| 20 | 31 |
About Andrey Filchenkov
Andrey Filchenkov is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Software, having authored 62 papers that have together received 360 indexed citations. Recurring topics across this work include Machine Learning and Data Classification (9 papers), Machine Learning and Algorithms (5 papers) and Generative Adversarial Networks and Image Synthesis (4 papers). The work is most often cited by research in Artificial Intelligence (147 citations), Computer Vision and Pattern Recognition (82 citations) and Information Systems (81 citations). Andrey Filchenkov has collaborated with scholars based in Russia, Finland and Singapore. Frequent co-authors include Aleksandr Farseev, Tat‐Seng Chua, Anatoly Shalyto, Valeriy Vyatkin, Evgeny Putin, Lidia Pivovarova, I. S. Lobanov, Kirill Kochetov, Sergey Nikolenko and Arip Asadulaev. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Access and Future Generation Computer Systems.
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.