Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Dmitrii Marin"'
Autor:
Dmitrii Marin, Jen-Hao Rick Chang, Anurag Ranjan, Anish Prabhu, Mohammad Rastegari, Oncel Tuzel
Publikováno v:
2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::20d0e1e932a314a9fec8e25a09da4dad
https://doi.org/10.1109/wacv56688.2023.00010
https://doi.org/10.1109/wacv56688.2023.00010
Publikováno v:
CVPR
We are interested in unsupervised reconstruction of complex near-capillary vasculature with thousands of bifurcations where supervision and learning are infeasible. Unsupervised methods can use many structural constraints, e.g. topology, geometry, ph
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c10b82930ad77b160693f7d4b518b07c
Publikováno v:
International Journal of Computer Vision. 127:477-511
This work bridges the gap between two popular methodologies for data partitioning: kernel clustering and regularization-based segmentation. While addressing closely related practical problems, these general methodologies may seem very different based
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::78d244fb73e5cece711e31f6d4d62e81
https://doi.org/10.1007/s11263-018-1115-1
https://doi.org/10.1007/s11263-018-1115-1
Publikováno v:
ICCV
Many automated processes such as auto-piloting rely on a good semantic segmentation as a critical component. To speed up performance, it is common to downsample the input frame. However, this comes at the cost of missed small objects and reduced accu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::26b2b28f6f911e8f21083ab5902f46d4
http://arxiv.org/abs/1907.07156
http://arxiv.org/abs/1907.07156
Publikováno v:
Bone and Joint Institute
CVPR
Medical Biophysics Publications
CVPR
Medical Biophysics Publications
© 2019 IEEE. We propose a new geometric regularization principle for reconstructing vector fields based on prior knowledge about their divergence. As one important example of this general idea, we focus on vector fields modelling blood flow pattern
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::72ce94acd5c737d182e43f2f7337886a
https://ir.lib.uwo.ca/boneandjointpub/358
https://ir.lib.uwo.ca/boneandjointpub/358
Publikováno v:
CVPR
The simplicity of gradient descent (GD) made it the default method for training ever-deeper and complex neural networks. Both loss functions and architectures are often explicitly tuned to be amenable to this basic local optimization. In the context
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bf3323c7148dc605c17ecc83541e6c9f
https://doi.org/10.1109/cvpr.2019.01043
https://doi.org/10.1109/cvpr.2019.01043
Kernel methods are popular in clustering due to their generality and discriminating power. However, we show that many kernel clustering criteria have density biases theoretically explaining some practically significant artifacts empirically observed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::359591fa70a6ec5ae0f183be44a30199
Publikováno v:
Computer Vision – ECCV 2016 ISBN: 9783319464749
ECCV (2)
ECCV (2)
We propose a new segmentation or clustering model that combines Markov Random Field (MRF) and Normalized Cut (NC) objectives. Both NC and MRF models are widely used in machine learning and computer vision, but they were not combined before due to sig
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::40c58271ee59e43c2c1e5e9fee6d09b1
https://doi.org/10.1007/978-3-319-46475-6_46
https://doi.org/10.1007/978-3-319-46475-6_46
Publikováno v:
ICCV
The log-likelihood energy term in popular model-fitting segmentation methods, e.g. [39, 8, 28, 10], is presented as a generalized "probabilistic K-means" energy [16] for color space clustering. This interpretation reveals some limitations, e.g. over-
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ced536374fcae434b3749e59f2ece9f3
https://doi.org/10.1109/iccv.2015.182
https://doi.org/10.1109/iccv.2015.182
Publikováno v:
Bone and Joint Institute
Medical Biophysics Publications
Medical Biophysics Publications
Many applications in vision require estimation of thin structures such as boundary edges, surfaces, roads, blood vessels, neurons, etc. Unlike most previous approaches, we simultaneously detect and delineate thin structures with sub-pixel localizatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6747ed1b353bf4ac11af5bc460ce4c6b
https://ir.lib.uwo.ca/boneandjointpub/386
https://ir.lib.uwo.ca/boneandjointpub/386