Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Calderón Ramírez, Saúl"'
Autor:
Perez-Rojas, Nelson, Calderon-Ramirez, Saul, Solis-Salazar, Martin, Romero-Sandoval, Mario, Arias-Monge, Monica, Saggion, Horacio
Text simplification, crucial in natural language processing, aims to make texts more comprehensible, particularly for specific groups like visually impaired Spanish speakers, a less-represented language in this field. In Spanish, there are few datase
Externí odkaz:
http://arxiv.org/abs/2312.09897
Semi-supervised learning (SSL) leverages both labeled and unlabeled data for training models when the labeled data is limited and the unlabeled data is vast. Frequently, the unlabeled data is more widely available than the labeled data, hence this da
Externí odkaz:
http://arxiv.org/abs/2211.02142
Deep learning methodologies have been employed in several different fields, with an outstanding success in image recognition applications, such as material quality control, medical imaging, autonomous driving, etc. Deep learning models rely on the ab
Externí odkaz:
http://arxiv.org/abs/2203.00190
In the context of the global coronavirus pandemic, different deep learning solutions for infected subject detection using chest X-ray images have been proposed. However, deep learning models usually need large labelled datasets to be effective. Semi-
Externí odkaz:
http://arxiv.org/abs/2109.00889
Autor:
Calderon-Ramirez, Saul, Murillo-Hernandez, Diego, Rojas-Salazar, Kevin, Elizondo, David, Yang, Shengxiang, Molina-Cabello, Miguel
The implementation of deep learning based computer aided diagnosis systems for the classification of mammogram images can help in improving the accuracy, reliability, and cost of diagnosing patients. However, training a deep learning model requires a
Externí odkaz:
http://arxiv.org/abs/2107.11696
Autor:
Zamora-Cardenas, Willard, Mendez, Mauro, Calderon-Ramirez, Saul, Vargas, Martin, Monge, Gerardo, Quiros, Steve, Elizondo, David, Molina-Cabello, Miguel A.
Cell instance segmentation in fluorescence microscopy images is becoming essential for cancer dynamics and prognosis. Data extracted from cancer dynamics allows to understand and accurately model different metabolic processes such as proliferation. T
Externí odkaz:
http://arxiv.org/abs/2106.05843
Autor:
Calderon-Ramirez, Saul, Oala, Luis
A common heuristic in semi-supervised deep learning (SSDL) is to select unlabelled data based on a notion of semantic similarity to the labelled data. For example, labelled images of numbers should be paired with unlabelled images of numbers instead
Externí odkaz:
http://arxiv.org/abs/2104.10223
Autor:
Calderon-Ramirez, Saul, Shengxiang-Yang, Moemeni, Armaghan, Elizondo, David, Colreavy-Donnelly, Simon, Chavarria-Estrada, Luis Fernando, Molina-Cabello, Miguel A.
The Corona Virus (COVID-19) is an internationalpandemic that has quickly propagated throughout the world. The application of deep learning for image classification of chest X-ray images of Covid-19 patients, could become a novel pre-diagnostic detect
Externí odkaz:
http://arxiv.org/abs/2008.08496
Autor:
Calderon-Ramirez, Saul, Oala, Luis, Torrents-Barrena, Jordina, Yang, Shengxiang, Moemeni, Armaghan, Samek, Wojciech, Molina-Cabello, Miguel A.
In this work, we propose MixMOOD - a systematic approach to mitigate effect of class distribution mismatch in semi-supervised deep learning (SSDL) with MixMatch. This work is divided into two components: (i) an extensive out of distribution (OOD) abl
Externí odkaz:
http://arxiv.org/abs/2006.07767
Autor:
Fuentes-Fino, Ricardo1 (AUTHOR), Calderón-Ramírez, Saúl2 (AUTHOR), Domínguez, Enrique1,3 (AUTHOR), López-Rubio, Ezequiel1,3 (AUTHOR), Elizondo, David4 (AUTHOR), Molina-Cabello, Miguel A.1,3 (AUTHOR) miguelangel@lcc.uma.es
Publikováno v:
Neural Computing & Applications. Oct2023, Vol. 35 Issue 30, p22151-22161. 11p.
