Artyom M. Grigoryan

2.2k citations
146 papers · 1.5k indexed · h-index 19
Topics
Image and Signal Denoising Methods (63 papers)Digital Filter Design and Implementation (36 papers)Mathematical Analysis and Transform Methods (25 papers)

In The Last Decade

Artyom M. Grigoryan

127 papers receiving 1.4k citations

Peers

Artyom M. Grigoryan
Comparison fields: 5 of 94
  • Computer Vision and Pattern Recognition 1.0k
  • Media Technology 346
  • Signal Processing 342
  • Applied Mathematics 191
  • Artificial Intelligence 167
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Citations per field
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Citations per year

Countries citing papers authored by Artyom M. Grigoryan

Since Specialization
Citations

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

Fields of papers citing papers by Artyom M. Grigoryan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Artyom M. Grigoryan. 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 Artyom M. Grigoryan. The network helps show where Artyom M. Grigoryan may publish in the future.

Co-authorship network of co-authors of Artyom M. Grigoryan

This figure shows the co-authorship network connecting the top 25 collaborators of Artyom M. Grigoryan. A scholar is included among the top collaborators of Artyom M. Grigoryan 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 Artyom M. Grigoryan. Artyom M. Grigoryan 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
#WorkIndexed citations
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10 35
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Implementation of FFT by using MATLAB: SIMULINK on Xilinx Virtex - 4 FPGAs: Performance of a Paired Transform Based FFT
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An optimal sequential optimization approach in application to dynamic weapon allocation in naval warfare
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Implementation of the DFT Using Radix-2 and Paired Transform Algorithms.
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About Artyom M. Grigoryan

Artyom M. Grigoryan is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Media Technology, having authored 146 papers that have together received 1.5k indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (63 papers), Digital Filter Design and Implementation (36 papers) and Mathematical Analysis and Transform Methods (25 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.0k citations), Media Technology (346 citations) and Signal Processing (342 citations). Artyom M. Grigoryan has collaborated with scholars based in United States, Armenia and Denmark. Frequent co-authors include Sos С. Agaian, Karen Panetta, Edward R. Dougherty, Fatma Taş Arslan, Galen Hostetter, Claus L. Andersen, Anne Kallioniemi, Guido Sauter, Olli Kallioniemi and Mehdi Hajinoroozi. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Image Processing and IEEE Transactions on Signal Processing.

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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