Dmitry Laptev

867 total citations
12 papers, 307 citations indexed

About

Dmitry Laptev is a scholar working on Computer Vision and Pattern Recognition, Biophysics and Cognitive Neuroscience. According to data from OpenAlex, Dmitry Laptev has authored 12 papers receiving a total of 307 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Vision and Pattern Recognition, 3 papers in Biophysics and 2 papers in Cognitive Neuroscience. Recurrent topics in Dmitry Laptev's work include Advanced Image and Video Retrieval Techniques (4 papers), Medical Image Segmentation Techniques (3 papers) and Cell Image Analysis Techniques (3 papers). Dmitry Laptev is often cited by papers focused on Advanced Image and Video Retrieval Techniques (4 papers), Medical Image Segmentation Techniques (3 papers) and Cell Image Analysis Techniques (3 papers). Dmitry Laptev collaborates with scholars based in Switzerland, Russia and United Kingdom. Dmitry Laptev's co-authors include Joachim M. Buhmann, Nikolay Savinov, Marc Pollefeys, Peter Achermann, Ximena Omlin, Alexander Malafeev, Adam Wichniak, Aleksandra Wierzbicka, Robert Riener and Stefan Bauer and has published in prestigious journals such as NeuroImage, Frontiers in Neuroscience and Biological Cybernetics.

In The Last Decade

Dmitry Laptev

11 papers receiving 298 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Dmitry Laptev Switzerland	6	156	101	43	40	38	12	307
Alfonso Alba Mexico	11	92 0.6×	206 2.0×	36 0.8×	25 0.6×	26 0.7×	48	415
Cristian Munteanu Portugal	10	244 1.6×	44 0.4×	13 0.3×	68 1.7×	33 0.9×	22	368
Yun Lu China	12	57 0.4×	121 1.2×	59 1.4×	73 1.8×	11 0.3×	40	381
Alvina Goh Singapore	10	215 1.4×	135 1.3×	12 0.3×	106 2.6×	13 0.3×	16	723
Yi Xia China	12	72 0.5×	181 1.8×	6 0.1×	44 1.1×	17 0.4×	30	392
Vamsi Krishna Ithapu United States	10	144 0.9×	54 0.5×	11 0.3×	114 2.9×	18 0.5×	37	457
Yunbo Tang China	11	53 0.3×	274 2.7×	25 0.6×	65 1.6×	13 0.3×	27	434
Corneliu Florea Romania	12	240 1.5×	58 0.6×	33 0.8×	30 0.8×	5 0.1×	69	363
Xixi Wang China	12	108 0.7×	115 1.1×	21 0.5×	112 2.8×	11 0.3×	26	427
Shan Cheng China	17	45 0.3×	51 0.5×	38 0.9×	46 1.1×	8 0.2×	57	621

Countries citing papers authored by Dmitry Laptev

Since Specialization

Citations

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

Fields of papers citing papers by Dmitry Laptev

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dmitry Laptev

This figure shows the co-authorship network connecting the top 25 collaborators of Dmitry Laptev. A scholar is included among the top collaborators of Dmitry Laptev 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 Dmitry Laptev. Dmitry Laptev is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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12 of 12 papers shown

1.

Malafeev, Alexander, Dmitry Laptev, Stefan Bauer, et al.. (2018). Automatic Human Sleep Stage Scoring Using Deep Neural Networks. Frontiers in Neuroscience. 12. 781–781. 107 indexed citations

2.

Laptev, Dmitry, Nikolay Savinov, Joachim M. Buhmann, & Marc Pollefeys. (2016). TI-POOLING: Transformation-Invariant Pooling for Feature Learning in Convolutional Neural Networks. 289–297. 146 indexed citations

3.

Laptev, Dmitry & Joachim M. Buhmann. (2015). Transformation-Invariant Convolutional Jungles. 3043–3051. 10 indexed citations

4.

Laptev, Dmitry, et al.. (2014). Superslicing frame restoration for anisotropic sstem. abs 1210 564. 1198–1201.

5.

Laptev, Dmitry, et al.. (2014). Parameter-free discovery and recommendation of areas-of-interest. 113–122. 10 indexed citations

6.

Laptev, Dmitry, et al.. (2013). Automatic determination of cell division rate using microscope images. Pattern Recognition and Image Analysis. 23(1). 105–110. 1 indexed citations

7.

Laptev, Dmitry, et al.. (2012). Anisotropic ssTEM Image Segmentation Using Dense Correspondence across Sections. Lecture notes in computer science. 15(Pt 1). 323–330. 18 indexed citations

8.

Laptev, Dmitry, et al.. (2011). Short-term solar flare forecast. 1 indexed citations

9.

Laptev, Dmitry, et al.. (2010). Variational segmentation algorithms with label frequency constraints. Pattern Recognition and Image Analysis. 20(3). 324–334. 4 indexed citations

10.

Laptev, Dmitry, et al.. (2006). Stability of the saccadic system. UCL Discovery (University College London). 2 indexed citations

11.

Laptev, Dmitry, Ozgur E. Akman, & Richard A. Clement. (2006). Stability of the saccadic oculomotor system. Biological Cybernetics. 95(3). 281–287. 6 indexed citations

12.

Laptev, Dmitry, Chloe Hutton, Ralf Deichmann, O. Josephs, & Robert Turner. (2001). Are fMRI realignment parameters contaminated by task-induced activation?. NeuroImage. 13(6). 24–24. 2 indexed citations

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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