Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Iglovikov, Vladimir"'
Autor:
Houston, John, Zuidhof, Guido, Bergamini, Luca, Ye, Yawei, Chen, Long, Jain, Ashesh, Omari, Sammy, Iglovikov, Vladimir, Ondruska, Peter
Motivated by the impact of large-scale datasets on ML systems we present the largest self-driving dataset for motion prediction to date, containing over 1,000 hours of data. This was collected by a fleet of 20 autonomous vehicles along a fixed route
Externí odkaz:
http://arxiv.org/abs/2006.14480
Autor:
Allan, Max, Kondo, Satoshi, Bodenstedt, Sebastian, Leger, Stefan, Kadkhodamohammadi, Rahim, Luengo, Imanol, Fuentes, Felix, Flouty, Evangello, Mohammed, Ahmed, Pedersen, Marius, Kori, Avinash, Alex, Varghese, Krishnamurthi, Ganapathy, Rauber, David, Mendel, Robert, Palm, Christoph, Bano, Sophia, Saibro, Guinther, Shih, Chi-Sheng, Chiang, Hsun-An, Zhuang, Juntang, Yang, Junlin, Iglovikov, Vladimir, Dobrenkii, Anton, Reddiboina, Madhu, Reddy, Anubhav, Liu, Xingtong, Gao, Cong, Unberath, Mathias, Kim, Myeonghyeon, Kim, Chanho, Kim, Chaewon, Kim, Hyejin, Lee, Gyeongmin, Ullah, Ihsan, Luna, Miguel, Park, Sang Hyun, Azizian, Mahdi, Stoyanov, Danail, Maier-Hein, Lena, Speidel, Stefanie
In 2015 we began a sub-challenge at the EndoVis workshop at MICCAI in Munich using endoscope images of ex-vivo tissue with automatically generated annotations from robot forward kinematics and instrument CAD models. However, the limited background va
Externí odkaz:
http://arxiv.org/abs/2001.11190
Autor:
Rakhlin, Alexander, Tiulpin, Aleksei, Shvets, Alexey A., Kalinin, Alexandr A., Iglovikov, Vladimir I., Nikolenko, Sergey
Breast cancer is one of the main causes of death worldwide. Histopathological cellularity assessment of residual tumors in post-surgical tissues is used to analyze a tumor's response to a therapy. Correct cellularity assessment increases the chances
Externí odkaz:
http://arxiv.org/abs/1905.01743
Autor:
Allan, Max, Shvets, Alex, Kurmann, Thomas, Zhang, Zichen, Duggal, Rahul, Su, Yun-Hsuan, Rieke, Nicola, Laina, Iro, Kalavakonda, Niveditha, Bodenstedt, Sebastian, Herrera, Luis, Li, Wenqi, Iglovikov, Vladimir, Luo, Huoling, Yang, Jian, Stoyanov, Danail, Maier-Hein, Lena, Speidel, Stefanie, Azizian, Mahdi
In mainstream computer vision and machine learning, public datasets such as ImageNet, COCO and KITTI have helped drive enormous improvements by enabling researchers to understand the strengths and limitations of different algorithms via performance c
Externí odkaz:
http://arxiv.org/abs/1902.06426
Source camera identification is the process of determining which camera or model has been used to capture an image. In the recent years, there has been a rapid growth of research interest in the domain of forensics. In the current work, we describe o
Externí odkaz:
http://arxiv.org/abs/1810.02981
Autor:
Buslaev, Alexander, Parinov, Alex, Khvedchenya, Eugene, Iglovikov, Vladimir I., Kalinin, Alexandr A.
Data augmentation is a commonly used technique for increasing both the size and the diversity of labeled training sets by leveraging input transformations that preserve output labels. In computer vision domain, image augmentations have become a commo
Externí odkaz:
http://arxiv.org/abs/1809.06839
Analysis of high-resolution satellite images has been an important research topic for traffic management, city planning, and road monitoring. One of the problems here is automatic and precise road extraction. From an original image, it is difficult a
Externí odkaz:
http://arxiv.org/abs/1806.05182
Semantic segmentation is in-demand in satellite imagery processing. Because of the complex environment, automatic categorization and segmentation of land cover is a challenging problem. Solving it can help to overcome many obstacles in urban planning
Externí odkaz:
http://arxiv.org/abs/1806.03510
The most common approaches to instance segmentation are complex and use two-stage networks with object proposals, conditional random-fields, template matching or recurrent neural networks. In this work we present TernausNetV2 - a simple fully convolu
Externí odkaz:
http://arxiv.org/abs/1806.00844
Publikováno v:
2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA)
Accurate detection and localization for angiodysplasia lesions is an important problem in early stage diagnostics of gastrointestinal bleeding and anemia. Gold-standard for angiodysplasia detection and localization is performed using wireless capsule
Externí odkaz:
http://arxiv.org/abs/1804.08024