Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Eduardo Pooch"'
Autor:
Camila Kolling, Martin More, Nathan Gavenski, Eduardo Pooch, Otavio Parraga, Rodrigo C. Barros
Publikováno v:
2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f987707caa3792b5680dd7a8cf04e5e3
https://doi.org/10.1109/wacv51458.2022.00263
https://doi.org/10.1109/wacv51458.2022.00263
Publikováno v:
IJCNN
Recently, learning-based approaches for 3D reconstruction from 2D images have gained popularity due to its modern applications, e.g., 3D printers, autonomous robots, self-driving cars, virtual reality, and augmented reality. The computer vision commu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ddc41a57d11cb4996b69e8afcc76732a
http://arxiv.org/abs/2008.04738
http://arxiv.org/abs/2008.04738
Publikováno v:
Intelligent Systems ISBN: 9783030613761
BRACIS
BRACIS
Radiography is a primary examination used to diagnose chest conditions, as it is fast, low cost, and widely available. If the physician cannot conclude de diagnosis with the radiography, a computed tomography scan may be required. However, this exam
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::04e9ee262a782269a0c7db366af1a5e8
https://doi.org/10.1007/978-3-030-61377-8_14
https://doi.org/10.1007/978-3-030-61377-8_14
Publikováno v:
Interpretable and Annotation-Efficient Learning for Medical Image Computing ISBN: 9783030611651
iMIMIC/MIL3ID/LABELS@MICCAI
iMIMIC/MIL3ID/LABELS@MICCAI
To train deep learning models in a supervised fashion, we need a significant amount of training data, but in most medical imaging scenarios, there is a lack of annotated data available. In this paper, we compare state-of-the-art semi-supervised class
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a69190dc7bf24be7fbaf094469d46d6b
https://doi.org/10.1007/978-3-030-61166-8_19
https://doi.org/10.1007/978-3-030-61166-8_19
Publikováno v:
Thoracic Image Analysis ISBN: 9783030624682
TIA@MICCAI
TIA@MICCAI
While deep learning models become more widespread, their ability to handle unseen data and generalize for any scenario is yet to be challenged. In medical imaging, there is a high heterogeneity of distributions among images based on the equipment tha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::49bdb6fd9081849ce8d749db2e54f62e
https://doi.org/10.1007/978-3-030-62469-9_7
https://doi.org/10.1007/978-3-030-62469-9_7
Publikováno v:
Intelligent Systems ISBN: 9783030613761
BRACIS
BRACIS
Early diagnosis of genetic syndromes has a vital importance in the prevention of any potential related health problems. Down syndrome is the most common genetic syndrome. Patients with down syndrome have a high probability of developmental disorders,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aea50a5f93c644e397773b6964e1ca53
https://doi.org/10.1007/978-3-030-61377-8_25
https://doi.org/10.1007/978-3-030-61377-8_25
Autor:
Marcia Regina Stech, Maria Helena Fermino, Eduardo Pooch, Paulo Cesar Abreu, Kelly Cristina Tagliari de Brito, Luis Alberto Romano, Silvio César Cazella, Lissandra Souto Cavalli, Arturo Sánchez-Paz, Benito Guimarães de Brito
Publikováno v:
Aquaculture Research. 49:2597-2602
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7949f8dbf33f3196be1e377bd4efa36d
https://doi.org/10.1111/are.13697
https://doi.org/10.1111/are.13697
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9783030017453
ISAmI
ISAmI
At the same time, it is necessary to constantly improve competences related to nursing care, there is a shortage of tools used for permanent education of the professionals involved in direct assistance of patients with central venous catheters, a pro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::226f7c9c947ff2f470f7d1336b8323cf
https://doi.org/10.1007/978-3-030-01746-0_6
https://doi.org/10.1007/978-3-030-01746-0_6