Zobrazeno 1 - 10
of 209
pro vyhledávání: '"Elizondo, David"'
Accurate and timely detection of cyber threats is critical to keeping our online economy and data safe. A key technique in early detection is the classification of unusual patterns of network behaviour, often hidden as low-frequency events within com
Externí odkaz:
http://arxiv.org/abs/2404.19121
Typical event datasets such as those used in network intrusion detection comprise hundreds of thousands, sometimes millions, of discrete packet events. These datasets tend to be high dimensional, stateful, and time-series in nature, holding complex l
Externí odkaz:
http://arxiv.org/abs/2310.09834
Autor:
Rivera, Antonio J., Dávila, Miguel A., Elizondo, David, del Jesus, María J., Charte, Francisco
Resampling algorithms are a useful approach to deal with imbalanced learning in multilabel scenarios. These methods have to deal with singularities in the multilabel data, such as the occurrence of frequent and infrequent labels in the same instance.
Externí odkaz:
http://arxiv.org/abs/2305.17152
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:
Elizondo, David C.
Wide-area disturbances are power outages occurring over large geographical regions that dramatically affect the power system reliability, causing interruptions of the electric supply to residential, commercial, and industrial users. Historically, wid
Externí odkaz:
http://hdl.handle.net/10919/26902
http://scholar.lib.vt.edu/theses/available/etd-04162003-202144/
http://scholar.lib.vt.edu/theses/available/etd-04162003-202144/
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