Zobrazeno 1 - 10
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pro vyhledávání: '"A. Rodriguez-Santiago"'
Autor:
Arvizu, Vanessa
Publikováno v:
Estudios Sociológicos, 2023 Sep 01. 41(123), 901-908.
Externí odkaz:
https://www.jstor.org/stable/27260802
Autor:
Das, Adrito, Khan, Danyal Z., Psychogyios, Dimitrios, Zhang, Yitong, Hanrahan, John G., Vasconcelos, Francisco, Pang, You, Chen, Zhen, Wu, Jinlin, Zou, Xiaoyang, Zheng, Guoyan, Qayyum, Abdul, Mazher, Moona, Razzak, Imran, Li, Tianbin, Ye, Jin, He, Junjun, Płotka, Szymon, Kaleta, Joanna, Yamlahi, Amine, Jund, Antoine, Godau, Patrick, Kondo, Satoshi, Kasai, Satoshi, Hirasawa, Kousuke, Rivoir, Dominik, Pérez, Alejandra, Rodriguez, Santiago, Arbeláez, Pablo, Stoyanov, Danail, Marcus, Hani J., Bano, Sophia
The field of computer vision applied to videos of minimally invasive surgery is ever-growing. Workflow recognition pertains to the automated recognition of various aspects of a surgery: including which surgical steps are performed; and which surgical
Externí odkaz:
http://arxiv.org/abs/2409.01184
Autor:
Pérez, Alejandra, Rodríguez, Santiago, Ayobi, Nicolás, Aparicio, Nicolás, Dessevres, Eugénie, Arbeláez, Pablo
Phase recognition in surgical videos is crucial for enhancing computer-aided surgical systems as it enables automated understanding of sequential procedural stages. Existing methods often rely on fixed temporal windows for video analysis to identify
Externí odkaz:
http://arxiv.org/abs/2407.17361
Quantum control techniques play an important role in manipulating and harnessing the properties of different quantum systems, including isolated atoms. Here, we propose to achieve quantum control over a single on-surface atomic spin using Landau-Zene
Externí odkaz:
http://arxiv.org/abs/2404.19036
Autor:
Ayobi, Nicolás, Rodríguez, Santiago, Pérez, Alejandra, Hernández, Isabela, Aparicio, Nicolás, Dessevres, Eugénie, Peña, Sebastián, Santander, Jessica, Caicedo, Juan Ignacio, Fernández, Nicolás, Arbeláez, Pablo
This paper presents the Holistic and Multi-Granular Surgical Scene Understanding of Prostatectomies (GraSP) dataset, a curated benchmark that models surgical scene understanding as a hierarchy of complementary tasks with varying levels of granularity
Externí odkaz:
http://arxiv.org/abs/2401.11174
Akademický článek
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Publikováno v:
International Journal of Manpower, 2024, Vol. 45, Issue 10, pp. 115-143.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/IJM-11-2023-0705
Autor:
Psychogyios, Dimitrios, Colleoni, Emanuele, Van Amsterdam, Beatrice, Li, Chih-Yang, Huang, Shu-Yu, Li, Yuchong, Jia, Fucang, Zou, Baosheng, Wang, Guotai, Liu, Yang, Boels, Maxence, Huo, Jiayu, Sparks, Rachel, Dasgupta, Prokar, Granados, Alejandro, Ourselin, Sebastien, Xu, Mengya, Wang, An, Wu, Yanan, Bai, Long, Ren, Hongliang, Yamada, Atsushi, Harai, Yuriko, Ishikawa, Yuto, Hayashi, Kazuyuki, Simoens, Jente, DeBacker, Pieter, Cisternino, Francesco, Furnari, Gabriele, Mottrie, Alex, Ferraguti, Federica, Kondo, Satoshi, Kasai, Satoshi, Hirasawa, Kousuke, Kim, Soohee, Lee, Seung Hyun, Lee, Kyu Eun, Kong, Hyoun-Joong, Fu, Kui, Li, Chao, An, Shan, Krell, Stefanie, Bodenstedt, Sebastian, Ayobi, Nicolas, Perez, Alejandra, Rodriguez, Santiago, Puentes, Juanita, Arbelaez, Pablo, Mohareri, Omid, Stoyanov, Danail
Surgical tool segmentation and action recognition are fundamental building blocks in many computer-assisted intervention applications, ranging from surgical skills assessment to decision support systems. Nowadays, learning-based action recognition an
Externí odkaz:
http://arxiv.org/abs/2401.00496
Autor:
Johns, Lucas, Rodriguez, Santiago
Neutrinos in core-collapse supernovae and neutron-star mergers are susceptible to flavor instabilities of three kinds: slow, fast, and collisional. Prior work has established mappings of the first two onto abstract mechanical systems in flavor space,
Externí odkaz:
http://arxiv.org/abs/2312.10340
Publikováno v:
2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI), 10230819
We propose Masked-Attention Transformers for Surgical Instrument Segmentation (MATIS), a two-stage, fully transformer-based method that leverages modern pixel-wise attention mechanisms for instrument segmentation. MATIS exploits the instance-level na
Externí odkaz:
http://arxiv.org/abs/2303.09514