|
|
Most published authors (scientific articles only) of the journal
|
| 1. |
V. V. Kotlyar |
123 |
| 2. |
A. A. Kovalev |
73 |
| 3. |
S. N. Khonina |
68 |
| 4. |
L. L. Doskolovich |
52 |
| 5. |
A. G. Nalimov |
49 |
| 6. |
S. S. Stafeev |
48 |
| 7. |
N. L. Kazanskii |
45 |
| 8. |
V. V. Myasnikov |
29 |
| 9. |
S. I. Kharitonov |
28 |
| 10. |
R. V. Skidanov |
27 |
| 11. |
A. P. Porfirev |
26 |
| 12. |
S. V. Karpeev |
24 |
| 13. |
D. A. Bykov |
23 |
| 14. |
E. S. Kozlova |
22 |
| 15. |
S. G. Volotovsky |
21 |
| 16. |
A. V. Kupriyanov |
20 |
| 17. |
V. V. Podlipnov |
20 |
| 18. |
Yu. V. Vizilter |
17 |
| 19. |
A. V. Volyar |
17 |
| 20. |
S. A. Degtyarev |
16 |
| 21. |
M. A. Moiseev |
16 |
| 22. |
A. V. Ustinov |
16 |
|
40 most published authors of the journal |
|
| Most cited authors of the journal |
| 1. |
N. L. Kazanskii |
652 |
| 2. |
S. N. Khonina |
593 |
| 3. |
V. V. Kotlyar |
574 |
| 4. |
A. A. Kovalev |
305 |
| 5. |
A. G. Nalimov |
290 |
| 6. |
S. I. Kharitonov |
287 |
| 7. |
L. L. Doskolovich |
285 |
| 8. |
S. S. Stafeev |
250 |
| 9. |
V. V. Podlipnov |
232 |
| 10. |
A. V. Kupriyanov |
221 |
| 11. |
R. V. Skidanov |
216 |
| 12. |
V. V. Arlazarov |
202 |
| 13. |
A. V. Volyar |
198 |
| 14. |
A. V. Nikonorov |
196 |
| 15. |
K. B. Bulatov |
180 |
| 16. |
Ya. E. Akimova |
179 |
| 17. |
N. A. Ivliev |
175 |
| 18. |
M. V. Bretsko |
174 |
| 19. |
S. V. Karpeev |
168 |
| 20. |
S. G. Volotovsky |
162 |
| 21. |
V. V. Myasnikov |
162 |
|
40 most cited authors of the journal |
|
| Most cited articles of the journal |
| 1. |
MIDV-500: a dataset for identity document analysis and recognition on mobile devices in video stream V. V. Arlazarov, K. B. Bulatov, T. S. Chernov, V. L. Arlazarov Computer Optics, 2019, 43:5, 818–824 |
90 |
| 2. |
Detection of objects in the images: from likelihood relationships towards scalable and efficient neural networks N. A. Andriyanov, V. E. Dementiev, A. G. Tashlinskiy Computer Optics, 2022, 46:1, 139–159 |
78 |
| 3. |
Image restoration in diffractive optical systems using deep learning and deconvolution A. V. Nikonorov, M. V. Petrov, S. A. Bibikov, V. V. Kutikova, A. A. Morozov, N. L. Kazanskiy Computer Optics, 2017, 41:6, 875–887 |
64 |
| 4. |
Injectional multilens molding parameters optimization N. L. Kazanskiy, I. S. Stepanenko, A. I. Khaimovich, S. V. Kravchenko, E. V. Byzov, M. A. Moiseev Computer Optics, 2016, 40:2, 203–214 |
61 |
| 5. |
Addressed fiber Bragg structures in quasi-distributed microwave-photonic sensor systems O. G. Morozov, A. Zh. Sakhabutdinov Computer Optics, 2019, 43:4, 535–543 |
59 |
| 6. |
On the use of a multi-raster input of one-dimensional signals in two-dimensional optical correlators M. S. Kuzmin, V. V. Davydov, S. A. Rogov Computer Optics, 2019, 43:3, 391–396 |
51 |
| 7. |
Russian traffic sign images dataset V. I. Shakhuro, A. S. Konushin Computer Optics, 2016, 40:2, 294–300 |
51 |
| 8. |
Hyperspectral image segmentation using dimensionality reduction and classical segmentation approaches E. V. Myasnikov Computer Optics, 2017, 41:4, 564–572 |
50 |
| 9. |
Achievements in the development of plasmonic waveguide sensors for measuring the refractive index N. L. Kazanskiy, M. Butt, S. A. Degtyarev, S. N. Khonina Computer Optics, 2020, 44:3, 295–318 |
47 |
| 10. |
A vector optical vortex generated and focused using a metalens V. V. Kotlyar, A. G. Nalimov Computer Optics, 2017, 41:5, 645–654 |
47 |
| 11. |
Optical elements based on silicon photonics M. Butt, S. N. Khonina, N. L. Kazanskiy Computer Optics, 2019, 43:6, 1079–1083 |
46 |
| 12. |
MIDV-2020: a comprehensive benchmark dataset for identity document analysis K. B. Bulatov, E. V. Emelianova, D. V. Tropin, N. S. Skoryukina, Y. S. Chernyshova, A. V. Sheshkus, S. A. Usilin, Z. Ming, J.-Ch. Burie, M. M. Luqman, V. V. Arlazarov Computer Optics, 2022, 46:2, 252–270 |
41 |
| 13. |
Method for forecasting changes in time series parameters in digital information management systems Yu. A. Kropotov, A. Yu. Proskuryakov, A. A. Belov Computer Optics, 2018, 42:6, 1093–1100 |
40 |
| 14. |
Vegetation type recognition in hyperspectral images using a conjugacy indicator S. A. Bibikov, N. L. Kazanskiy, V. A. Fursov Computer Optics, 2018, 42:5, 846–854 |
40 |
| 15. |
Modeling the performance of a spaceborne hyperspectrometer based on the Offner scheme N. L. Kazanskiy, S. I. Kharitonov, L. L. Doskolovich, A. V. Pavelev Computer Optics, 2015, 39:1, 70–76 |
40 |
| 16. |
Crop growth monitoring through Sentinel and Landsat data based NDVI time-series M. Boori, K. Choudhary, A. V. Kupriyanov Computer Optics, 2020, 44:3, 409–419 |
37 |
| 17. |
Characteristics of sharp focusing of vortex Laguerre-Gaussian beams D. A. Savelyev, S. N. Khonina Computer Optics, 2015, 39:5, 654–662 |
37 |
| 18. |
Investigation of algorithms for coagulate arrangement in fundus images A. S. Shirokanev, D. V. Kirsh, N. Yu. Ilyasova, A. V. Kupriyanov Computer Optics, 2018, 42:4, 712–721 |
36 |
| 19. |
U-Net-bin: hacking the document image binarization contest P. V. Bezmaternykh, D. A. Ilin, D. P. Nikolaev Computer Optics, 2019, 43:5, 825–832 |
35 |
| 20. |
Reconstruction of anatomical structures using statistical shape modeling N. A. Smelkina, R. N. Kosarev, A. V. Nikonorov, I. M. Bairikov, K. N. Ryabov, E. V. Avdeev, N. L. Kazanskiy Computer Optics, 2017, 41:6, 897–904 |
35 |
|
40 most cited articles of the journal |
|
| Most requested articles of the journal |
|
|
| 1. |
Screen recapture detection based on color-texture analysis of document boundary regions I. A. Kunina, A. V. Sher, D. P. Nikolaev Computer Optics, 2023, 47:4, 650–657 | 58 |
| 2. |
Angular momentum of a light field as superposition of Hermite-Gaussian modes V. G. Volostnikov Computer Optics, 2015, 39:4, 459–461 | 37 |
| 3. |
Review of the current methods for robust image hashing A. V. Kozachok, S. A. Kopylov, R. V. Mescheriakov, O. O. Evsyutin Computer Optics, 2017, 41:5, 743–755 | 34 |
| 4. |
A nonparametric algorithm for automatic classification of large multivariate statistical data sets and its application I. V. Zenkov, A. V. Lapko, А. L. Vasily, S. T. Im, V. P. Tuboltsev, V. L. Avdeenok Computer Optics, 2021, 45:2, 253–260 | 32 |
| 5. |
An algorithm for mapping flooded areas through analysis of satellite imagery and terrestrial relief features O. A. Efremova, Yu. N. Kunakov, S. V. Pavlov, A. Kh. Sultanov Computer Optics, 2018, 42:4, 695–703 | 31 |
| 6. |
Spectral-spatial classification with k-means++ particional clustering E. A. Zimichev, N. L. Kazanskii, P. G. Serafimovich Computer Optics, 2014, 38:2, 281–286 | 29 |
| 7. |
Extrinsic calibration of stereo camera and three-dimensional laser scanner A. A. Abramenko Computer Optics, 2019, 43:2, 220–230 | 28 |
| 8. |
Neural network model for video-based face recognition with frames quality assessment M. Yu. Nikitin, V. S. Konouchine, A. S. Konouchine Computer Optics, 2017, 41:5, 732–742 | 27 |
| 9. |
Characterization of the surface relief of film diffractive optical elements T. P. Kaminskaya, V. V. Popov, A. M. Saletskiy Computer Optics, 2016, 40:2, 215–224 | 24 |
| 10. |
Earth remote sensing imagery classification using a multi-sensor super-resolution fusion algorithm A. M. Belov, A. Yu. Denisova Computer Optics, 2020, 44:4, 627–635 | 23 |
|
| Total publications: |
1232 |
| Scientific articles: |
1219 |
| Authors: |
1621 |
| Citations: |
7338 |
| Cited articles: |
960 |
 |
Impact Factor Web of Science |
|
for 2025:
1.100 |
|
for 2024:
1.200 |
|
for 2023:
1.100 |
 |
Scopus Metrics |
|
2025 |
CiteScore |
3.200 |
|
2025 |
SNIP |
0.636 |
|
2025 |
SJR |
0.280 |
|
2024 |
CiteScore |
3.800 |
|
2024 |
SNIP |
0.710 |
|
2024 |
SJR |
0.265 |
|
2023 |
CiteScore |
4.200 |
|
2023 |
SNIP |
0.575 |
|
2023 |
SJR |
0.251 |
|
2022 |
SJR |
0.321 |
|
2021 |
SJR |
0.508 |
|
2020 |
SJR |
0.491 |
|
2019 |
SJR |
0.586 |
|
2018 |
CiteScore |
2.370 |
|
2018 |
SJR |
0.535 |
|
2017 |
CiteScore |
1.790 |
|
2017 |
SNIP |
1.681 |
|
2017 |
SJR |
0.457 |
|
2016 |
CiteScore |
1.610 |
|
2016 |
SNIP |
1.495 |
|
2016 |
SJR |
0.348 |
|
2015 |
CiteScore |
1.220 |
|
2015 |
SNIP |
1.261 |
|
2015 |
IPP |
1.185 |
|
2015 |
SJR |
0.445 |
|
2014 |
CiteScore |
0.730 |
|
2014 |
SNIP |
0.846 |
|
2014 |
IPP |
0.656 |
|
2014 |
SJR |
0.285 |
|
2013 |
SNIP |
0.397 |
|
2013 |
IPP |
0.341 |
|
2013 |
SJR |
0.198 |
|