Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Anibal Pedraza"'
Publikováno v:
Algorithms, Vol 17, Iss 3, p 97 (2024)
HER2 overexpression is a prognostic and predictive factor observed in about 15% to 20% of breast cancer cases. The assessment of its expression directly affects the selection of treatment and prognosis. The measurement of HER2 status is performed by
Externí odkaz:
https://doaj.org/article/6e0e74c891a340359652c1b4e0c21a12
Publikováno v:
Applied Sciences, Vol 13, Iss 17, p 9527 (2023)
Microscopy scanners and artificial intelligence (AI) techniques have facilitated remarkable advancements in biomedicine. Incorporating these advancements into clinical practice is, however, hampered by the variety of digital file formats used, which
Externí odkaz:
https://doaj.org/article/3d985301d04442cea6bc9d2532b974ac
Publikováno v:
Symmetry, Vol 13, Iss 5, p 817 (2021)
One of the most intriguing phenomenons related to deep learning is the so-called adversarial examples. These samples are visually equivalent to normal inputs, undetectable for humans, yet they cause the networks to output wrong results. The phenomeno
Externí odkaz:
https://doaj.org/article/226a51b167274708a9e37ce4178686d5
Publikováno v:
Entropy, Vol 22, Iss 11, p 1201 (2020)
Adversarial examples are one of the most intriguing topics in modern deep learning. Imperceptible perturbations to the input can fool robust models. In relation to this problem, attack and defense methods are being developed almost on a daily basis.
Externí odkaz:
https://doaj.org/article/42d877ebfcd94449acfacdafbff3a0ac
Autor:
Jaime Gallego, Anibal Pedraza, Samuel Lopez, Georg Steiner, Lucia Gonzalez, Arvydas Laurinavicius, Gloria Bueno
Publikováno v:
Journal of Imaging, Vol 4, Iss 1, p 20 (2018)
Glomerulus classification and detection in kidney tissue segments are key processes in nephropathology used for the correct diagnosis of the diseases. In this paper, we deal with the challenge of automating Glomerulus classification and detection fro
Externí odkaz:
https://doaj.org/article/4dc0dd70df1a4695ab677525cb76f93d
Autor:
Gloria Bueno, Oscar Deniz, Anibal Pedraza, Jesús Ruiz-Santaquiteria, Jesús Salido, Gabriel Cristóbal, María Borrego-Ramos, Saúl Blanco
Publikováno v:
Applied Sciences, Vol 7, Iss 8, p 753 (2017)
This paper deals with automatic taxa identification based on machine learning methods. The aim is therefore to automatically classify diatoms, in terms of pattern recognition terminology. Diatoms are a kind of algae microorganism with high biodiversi
Externí odkaz:
https://doaj.org/article/f90eaf74060f4518a0687746c85a2384
Autor:
Anibal Pedraza, Gloria Bueno, Oscar Deniz, Gabriel Cristóbal, Saúl Blanco, María Borrego-Ramos
Publikováno v:
Applied Sciences, Vol 7, Iss 5, p 460 (2017)
Diatoms, a kind of algae microorganisms with several species, are quite useful for water quality determination, one of the hottest topics in applied biology nowadays. At the same time, deep learning and convolutional neural networks (CNN) are becomin
Externí odkaz:
https://doaj.org/article/7fc0b8ecc3b84d5aaff722475529f437
Akademický článek
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Publikováno v:
International Journal of Machine Learning and Cybernetics. 13:1065-1077
The phenomenon of Adversarial Examples has become one of the most intriguing topics associated to deep learning. The so-called adversarial attacks have the ability to fool deep neural networks with inappreciable perturbations. While the effect is str
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fa267d070e7fe25eedf7c49e85963185
https://doi.org/10.1007/s13042-021-01435-0
https://doi.org/10.1007/s13042-021-01435-0
Hyperdeep: Comparison of Ai-Based Methods for Predicting Chemical Components in Hyperspectral Images
Autor:
Alberto Velasco-Mata, Noelia Vallez, Jesus Ruiz-Santaquiteria, Anibal Pedraza, Oscar Deniz, Gloria Bueno
Publikováno v:
2022 IEEE International Conference on Image Processing (ICIP).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2f08e1db161de59ea18789c4664510c0
https://doi.org/10.1109/icip46576.2022.9897549
https://doi.org/10.1109/icip46576.2022.9897549