Zobrazeno 1 - 10
of 70
pro vyhledávání: '"Raul E. Sanchez-Yanez"'
Autor:
Edgar F. Duque-Vazquez, Raul E. Sanchez-Yanez, Noe Saldaña-Robles, Ma. Fabiola León-Galván, Jonathan Cepeda-Negrete
Publikováno v:
Heliyon, Vol 10, Iss 5, Pp e26520- (2024)
Computational cell segmentation is a vital area of research, particularly in the analysis of images of cancer cells. The use of cell lines, such as the widely utilized HeLa cell line, is crucial for studying cancer. While deep learning algorithms hav
Externí odkaz:
https://doaj.org/article/32e4b7456c554f299613f6ed103789f7
Autor:
Rocio A. Lizarraga-Morales, Fernando E. Correa-Tome, Raul E. Sanchez-Yanez, Jonathan Cepeda-Negrete
Publikováno v:
IEEE Access, Vol 7, Pp 18042-18049 (2019)
The quality assurance of fabrics is a fundamental issue in the textile manufacturing industry. Automatic and accurate detection of defects is one of the most important and challenging tasks in order to guarantee the quality of fabrics. In this paper,
Externí odkaz:
https://doaj.org/article/ab2f484edfdc4329a403f2dbc2b9c734
Publikováno v:
Diagnostics, Vol 12, Iss 7, p 1528 (2022)
The incapability to move the facial muscles is known as facial palsy, and it affects various abilities of the patient, for example, performing facial expressions. Recently, automatic approaches aiming to diagnose facial palsy using images and machine
Externí odkaz:
https://doaj.org/article/ecf03c58aa2049e2a558a5864f0e3722
Publikováno v:
Healthcare, Vol 10, Iss 4, p 659 (2022)
Humans express their emotions verbally and through actions, and hence emotions play a fundamental role in facial expressions and body gestures. Facial expression recognition is a popular topic in security, healthcare, entertainment, advertisement, ed
Externí odkaz:
https://doaj.org/article/67cb71dfb1ec4b728226526f050e5e34
Autor:
Jonathan Cepeda-Negrete, Raul E. Sanchez-Yanez, Fernando E. Correa-Tome, Rocio A. Lizarraga-Morales
Publikováno v:
IEEE Access, Vol 6, Pp 14935-14945 (2018)
In this paper, we introduce an image enhancing approach for transforming dark images into lightened scenes, and we evaluate such method in different perceptual color spaces, in order to find the best-suited for this particular task. Specifically, we
Externí odkaz:
https://doaj.org/article/6bce24d631164e0ca4e9ad2362668cdc
Publikováno v:
IEEE Access, Vol 5, Pp 15390-15399 (2017)
This paper represents a twofold approach. On the one hand, we introduce a simple method that encompasses an ensemble of image processing algorithms with a multilevel color transfer approach at its core. On the other hand, the method is applied for pr
Externí odkaz:
https://doaj.org/article/d5a6a3c512d844329732ce54bed9e45d
Publikováno v:
Applied Sciences, Vol 11, Iss 5, p 2435 (2021)
The inability to move the muscles of the face on one or both sides is known as facial paralysis, which may affect the ability of the patient to speak, blink, swallow saliva, eat, or communicate through natural facial expressions. The well-being of th
Externí odkaz:
https://doaj.org/article/26a454bd1de6483fadda66eda238bc2b
Autor:
Alberto Lopez-Alanis, Rocio A. Lizarraga-Morales, Raul E. Sanchez-Yanez, Diana E. Martinez-Rodriguez, Marco A. Contreras-Cruz
Publikováno v:
Applied Sciences, Vol 9, Iss 10, p 2015 (2019)
In this paper, we propose an approach for salient pixel detection using a rule-based system. In our proposal, rules are automatically learned by combining four saliency models. The learned rules are utilized for the detection of pixels of the salient
Externí odkaz:
https://doaj.org/article/643cbdba973740a3821854a28f80c7f4
Autor:
Victor Ayala-Ramirez, Raul E. Sanchez-Yanez, Felipe Trujillo-Romero, Rocio A. Lizarraga-Morales, Marco A. Contreras-Cruz, Alberto Lopez-Alanis
Publikováno v:
Applied Intelligence. 50:1745-1762
The visual saliency detection consists in determining the relevant visual information in a scene to segment it from the background. This paper proposes visual saliency detection in a rule-based approach using the image similarity cue to improve salie
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::53e3a64258e2155d98af197fac7e71f9
https://doi.org/10.1007/s10489-019-01582-6
https://doi.org/10.1007/s10489-019-01582-6
