Vasily Sachnev
- Computer Vision and Pattern Recognition top 1%
- Artificial Intelligence
- Signal Processing top 10%
- Computer Graphics and Computer-Aided Design top 10%
- Information Systems
- Co-authors
- Jeho NamYun Q. ShiSuresh SundaramHyon‐Gon ChooHyoung Joong KimSuah KimXiaochao QuRongyue Zhang
- Topics
- Chaos-based Image/Signal Encryption (10 papers)Advanced Steganography and Watermarking Techniques (10 papers)Machine Learning and ELM (9 papers)
- Cited by
- Computer Vision and Pattern RecognitionComputer Graphics and Computer-Aided DesignSignal Processing
- Journals
- IEEE Transactions on Information TheoryBMC BioinformaticsIEEE Transactions on Circuits and Systems for Video Technology
- Partner nations
- South KoreaSingaporeUnited States
In The Last Decade
Vasily Sachnev
22 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 45
- Computer Vision and Pattern Recognition 1.1k
- Artificial Intelligence 57
- Signal Processing 44
- Computer Graphics and Computer-Aided Design 27
- Information Systems 20
Countries citing papers authored by Vasily Sachnev
This map shows the geographic impact of Vasily Sachnev'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 Vasily Sachnev with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vasily Sachnev more than expected).
Fields of papers citing papers by Vasily Sachnev
This network shows the impact of papers produced by Vasily Sachnev. 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 Vasily Sachnev. The network helps show where Vasily Sachnev may publish in the future.
Co-authorship network of co-authors of Vasily Sachnev
This figure shows the co-authorship network connecting the top 25 collaborators of Vasily Sachnev. A scholar is included among the top collaborators of Vasily Sachnev 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 Vasily Sachnev. Vasily Sachnev is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 9 | |
| 7 | 11 | |
| 8 | 2 | |
| 9 | 1 | |
| 10 | 3 | |
| 11 | 1 | |
| 12 | 2 | |
| 13 | 9 | |
| 14 | 6 | |
| 15 | 7 | |
| 16 | 20 | |
| 17 | 37 | |
| 18 | 11 | |
| 19 | Reversible Watermarking Algorithm Using Sorting and Predictionbreakdown → | 637 |
| 20 | 270 |
About Vasily Sachnev
Vasily Sachnev is a scholar working on Health Informatics, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 24 papers that have together received 1.2k indexed citations. Recurring topics across this work include Chaos-based Image/Signal Encryption (10 papers), Advanced Steganography and Watermarking Techniques (10 papers) and Machine Learning and ELM (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.1k citations), Computer Graphics and Computer-Aided Design (27 citations) and Signal Processing (44 citations). Vasily Sachnev has collaborated with scholars based in South Korea, Singapore and United States. Frequent co-authors include Jeho Nam, Yun Q. Shi, Suresh Sundaram, Hyon‐Gon Choo, Hyoung Joong Kim, Suah Kim, Xiaochao Qu, Rongyue Zhang, Jun Heo and Wenjia Xu. Their work appears in journals such as IEEE Transactions on Information Theory, BMC Bioinformatics and IEEE Transactions on Circuits and Systems for Video Technology.
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.