Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Dmitry Laptev"'
Autor:
Alexander Malafeev, Dmitry Laptev, Stefan Bauer, Ximena Omlin, Aleksandra Wierzbicka, Adam Wichniak, Wojciech Jernajczyk, Robert Riener, Joachim Buhmann, Peter Achermann
Publikováno v:
Frontiers in Neuroscience, Vol 12 (2018)
The classification of sleep stages is the first and an important step in the quantitative analysis of polysomnographic recordings. Sleep stage scoring relies heavily on visual pattern recognition by a human expert and is time consuming and subjective
Externí odkaz:
https://doaj.org/article/a74c0da8322a426bb63df59b70e007c5
Publikováno v:
Endocrine Abstracts.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1cdfb7c806424f3bc7ef5a6eda406878
https://doi.org/10.1530/endoabs.90.ep450
https://doi.org/10.1530/endoabs.90.ep450
Autor:
Elena Sechko, Elizaveta Raykina, Tamara Kuraeva, Dmitry Laptev, Olga Bezlepkina, Valentina Peterkova
Publikováno v:
Endocrine Abstracts.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::71d94125ccecb4dd57eb9c6a262d29e0
https://doi.org/10.1530/endoabs.90.ep304
https://doi.org/10.1530/endoabs.90.ep304
Publikováno v:
Pattern Recognition and Image Analysis. 23:105-110
Estimating the dynamics of cell culture development using fluorescent microscopy images is of great interest in modern cellular and molecular biology. In large-scale studies of cell populations involving a great number of images taken within a certai
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9f2b1152864cd6ecec9cd7ffd68f9a76
https://doi.org/10.1134/s1054661813010094
https://doi.org/10.1134/s1054661813010094
Autor:
Dmitry Laptev, Joachim M. Buhmann
Publikováno v:
Neural Connectomics Challenge ISBN: 9783319530697
Neural Connectomics
JMLR Workshop and Conference Proceedings
Challenges in Machine Learning Volume 11: Connectomics (ECML 2014)
Neural Connectomics
JMLR Workshop and Conference Proceedings
Challenges in Machine Learning Volume 11: Connectomics (ECML 2014)
JMLR Workshop and Conference Proceedings
ISSN:1938-7228
Challenges in Machine Learning Volume 11: Connectomics (ECML 2014)
ISSN:1938-7228
Challenges in Machine Learning Volume 11: Connectomics (ECML 2014)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c83aa0d4465d027fcbeddc90f69e2591
https://doi.org/10.1007/978-3-319-53070-3_9
https://doi.org/10.1007/978-3-319-53070-3_9
Publikováno v:
Pattern Recognition and Image Analysis. 20:324-334
We consider image and signal segmentation problems within the Markov random field (MRF) approach and try to take into account label frequency constraints. Incorporating these constraints into MRF leads to an NP-hard optimization problem. For solving
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::edcbd7f1ca53f08f6567ec7f9549454b
https://doi.org/10.1134/s1054661810030089
https://doi.org/10.1134/s1054661810030089
Autor:
Dan Ciresan, Dmitry Laptev, H. Sebastian Seung, Albert Cardona, Radim Burget, Alessandro Giusti, Johannes Schindelin, Luca Maria Gambardella, Lee Kamentsky, Tolga Tasdizen, Joachim M. Buhmann, Mojtaba Seyedhosseini, Ignacio Arganda-Carreras, Mustafa Gökhan Uzunbas, Ting Liu, Jürgen Schmidhuber, Vaclav Uher, Tuan D. Pham, Changming Sun, Daniel R. Berger, Srinivas C. Turaga, Erhan Bas, Sarvesh Dwivedi, Xiao Tan
Publikováno v:
Frontiers in Neuroanatomy, Vol 9 (2015)
Frontiers in Neuroanatomy
Frontiers in Neuroanatomy, Frontiers, 2015, 9, pp.142. ⟨10.3389/fnana.2015.00142⟩
Frontiers in Neuroanatomy (9), 142. (2015)
Frontiers in Neuroanatomy, 9
Frontiers
Frontiers in Neuroanatomy
Frontiers in Neuroanatomy, Frontiers, 2015, 9, pp.142. ⟨10.3389/fnana.2015.00142⟩
Frontiers in Neuroanatomy (9), 142. (2015)
Frontiers in Neuroanatomy, 9
Frontiers
To stimulate progress in automating the reconstruction of neural circuits, we organized the first international challenge on 2D segmentation of electron microscopic (EM) images of the brain. Participants submitted boundary maps predicted for a test s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bc28170091bbaac2167bf8d717747565
Autor:
Dmitry Laptev, Joachim M. Buhmann
Publikováno v:
CVPR
Many Computer Vision problems arise from information processing of data sources with nuisance variances like scale, orientation, contrast, perspective foreshortening or - in medical imaging - staining and local warping. In most cases these variances
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a9e93ac467be2a2b3f032286f9129354
https://doi.org/10.1109/cvpr.2015.7298923
https://doi.org/10.1109/cvpr.2015.7298923
Publikováno v:
SIGSPATIAL/GIS
The task of discovering places of interest is a key step for many location-based recommendation tasks. In this paper we propose a fully unsupervised and parameter-free approach to deal with this problem based on the collection of geotagged photos. Wh
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::466048e4db269b4dc14c2eb69c251d2b
https://doi.org/10.1145/2666310.2666416
https://doi.org/10.1145/2666310.2666416
Publikováno v:
ISBI
In biological imaging the data is often represented by a sequence of anisotropic frames — the resolution in one dimension is significantly lower than in the other dimensions. E.g. in electron microscopy it arises from the thickness of a scanned sec
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::81fb2b7d44eb791acff8df536c1803cb
https://doi.org/10.1109/isbi.2014.6868090
https://doi.org/10.1109/isbi.2014.6868090