Zobrazeno 1 - 10
of 161
pro vyhledávání: '"Roberto de Alencar Lotufo"'
Publikováno v:
Scientia Agricola, Vol 60, Iss 2, Pp 403-408 (2003)
For several decades, beef carcass evaluation for grading or research purposes has relied upon subjective visual scores, and manually taken measurements, but in recent times there has been a growing interest in new technologies capable of improving ac
Externí odkaz:
https://doaj.org/article/30015e54571448cba299428694c4614a
Publikováno v:
ICAIL
There has been mounting evidence that pretrained language models fine-tuned on large and diverse supervised datasets can transfer well to a variety of out-of-domain tasks. In this work, we investigate this transfer ability to the legal domain. For th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::559e4e1d904126a01d6ee16c54dd8330
Autor:
Irene Fantini, Lívia Rodrigues, Rodrigo Nogueira, Roberto de Alencar Lotufo, Diedre Carmo, Leticia Rittner, Israel Campiotti, Daniel Moraes, Gustavo Retuci Pinheiro
Publikováno v:
Health informatics journal. 27(3)
The COVID-19 pandemic generated research interest in automated models to perform classification and segmentation from medical imaging of COVID-19 patients, However, applications in real-world scenarios are still needed. We describe the development an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fb20cff4441a8e0f6298b897578db63a
https://pubmed.ncbi.nlm.nih.gov/34510949
https://pubmed.ncbi.nlm.nih.gov/34510949
Autor:
Roberto de Alencar Lotufo, Leticia Rittner, Bruna Gonçalves da Silva, Alzheimer's Disease Neuroimaging Initiative, Clarissa L. Yasuda, Diedre Carmo
Publikováno v:
Heliyon
Heliyon, Vol 7, Iss 2, Pp e06226-(2021)
Heliyon, Vol 7, Iss 2, Pp e06226-(2021)
Background: Hippocampus segmentation on magnetic resonance imaging is of key importance for the diagnosis, treatment decision and investigation of neuropsychiatric disorders. Automatic segmentation is an active research field, with many recent models
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7833e54e4654e6570033b476492a1936
https://pubmed.ncbi.nlm.nih.gov/33659748
https://pubmed.ncbi.nlm.nih.gov/33659748
Autor:
Roberto de Alencar Lotufo, Leticia Rittner, Mariana Eugênia de Carvalho Pereira, Irene Fantini
Publikováno v:
Medical Imaging 2020: Computer-Aided Diagnosis.
Current techniques trying to predict Alzheimer's disease at an early-stage explore the structural information of T1-weighted MR Images. Among these techniques, deep convolutional neural network (CNN) is the most promising since it has been successful
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::56955c7faf83cd349f7d780ae393031d
https://doi.org/10.1117/12.2550753
https://doi.org/10.1117/12.2550753
Autor:
Diedre Carmo, Gustavo Retuci Pinheiro, Leticia Rittner, Clarissa Lyn Yasuda, Roberto de Alencar Lotufo
Publikováno v:
Computational Diffusion MRI ISBN: 9783030528928
Convolutional neural networks have become a powerful tool for MRI brain analysis and are the state-of-the-art in the matter of brain structure segmentation. Despite the deep learning power and advantages, most of the work is still done in classical m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b615e9ece1ec745dd4018ff8deaa0879
https://doi.org/10.1007/978-3-030-52893-5_12
https://doi.org/10.1007/978-3-030-52893-5_12
Publikováno v:
Intelligent Systems ISBN: 9783030613761
BRACIS
BRACIS
Recent advances in language representation using neural networks have made it viable to transfer the learned internal states of large pretrained language models (LMs) to downstream natural language processing (NLP) tasks. This transfer learning appro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::20425d67eec166b9b48ff5b3c4f34143
https://doi.org/10.1007/978-3-030-61377-8_28
https://doi.org/10.1007/978-3-030-61377-8_28
Autor:
Julia Garrafa, David G. Gobbi, Leticia Rittner, Simone Appenzeller, Richard Frayne, Roberto de Alencar Lotufo, Marina Saluzzi, Oeslle Lucena, Roberto Souza
Publikováno v:
NeuroImage. 170:482-494
This paper presents an open, multi-vendor, multi-field strength magnetic resonance (MR) T1-weighted volumetric brain imaging dataset, named Calgary-Campinas-359 (CC-359). The dataset is composed of images of older healthy adults (29–80 years) acqui
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::478e212a4f686d86ff851736dc3d6f2e
https://doi.org/10.1016/j.neuroimage.2017.08.021
https://doi.org/10.1016/j.neuroimage.2017.08.021
Autor:
Roberto de Alencar Lotufo, Irene Fantini, Leticia Rittner, Mariana P. Bento, Fernando Cendes, Clarissa L. Yasuda
Publikováno v:
Computerized Medical Imaging and Graphics. 90:101897
Motion artifacts on magnetic resonance (MR) images degrade image quality and thus negatively affect clinical and research scanning. Considering the difficulty in preventing patient motion during MR examinations, the identification of motion artifact
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b07d4d44e89e364c9fb7676900c803e3
https://doi.org/10.1016/j.compmedimag.2021.101897
https://doi.org/10.1016/j.compmedimag.2021.101897
Publikováno v:
SoftwareX, Vol 6, Iss, Pp 81-84 (2017)
The iamxt is an array-based max-tree toolbox implemented in Python using the NumPy library for array processing. It has state of the art methods for building and processing the max-tree, and a large set of visualization tools that allow to view the t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e819ee0880e8386d0035c176c788784a