Yusbel Chávez Castilla (7C12-E3FE-7A09)

Curriculum Vitae

Yusbel Chávez Castilla

Yusbel Chávez Castilla is a Senior Development Technician specializing in the field of computer vision in the CVIG (Computer Vision, Interaction and Graphics) applied research department of the Center for Computer Graphics, University of Minho, Portugal. His main functions are the project manager and the technical development of projects. He also carries out research in the areas of computer vision/image processing/artificial intelligence. At an academic level, he graduated in Computer Engineering and received a master's degree in Applied Informatics from the Ciego de Avila University, Cuba.At a professional level, he has been involved in several projects that cover different areas of knowledge, namely: computer vision/image processing, artificial intelligence, database systems and has taught programming languages and database systems. Currently works as a Project Manager and develops projects in the area of computer vision and machine learning applied to images, subareas of intervention at CVIG.

Ler resumo completo ↓

Identificação

Identificação pessoal

Nome completo: Yusbel Chávez Castilla

Nomes de citação

Castilla, Yusbel

Identificadores de autor

Ciência ID: 7C12-E3FE-7A09
ORCID iD: 0000-0002-3436-7578

Domínios de atuação

Ciências Exatas - Ciências da Computação e da Informação

Idiomas

Idioma	Conversação	Leitura	Escrita	Compreensão	Peer-review
Espanhol; Castelhano (Idioma materno)
Inglês	Utilizador independente (B1)	Utilizador independente (B1)	Utilizador independente (B1)	Utilizador independente (B1)	Utilizador independente (B1)
Português	Utilizador independente (B2)	Utilizador independente (B2)	Utilizador independente (B2)	Utilizador independente (B2)	Utilizador independente (B2)

Formação

	Grau	Classificação
2011 Concluído	Maestría en Informática Aplicada (Master) Universidad de Ciego de Avila, Cuba
2009 Concluído	Ingeniería Informática (Licence) Especialização em Informática Universidad de Ciego de Avila, Cuba

Percurso profissional

Ciência

	Categoria Profissional Instituição de acolhimento	Empregador
2019 - 2024	Investigador Contratado (Investigação)	Centro de Computação Gráfica, Portugal

2019 - 2019	Estagiário de Investigação (Investigação)	Centro de Computação Gráfica, Portugal

Docência no Ensino Superior

	Categoria Profissional Instituição de acolhimento	Empregador
2009 - 2017	Professor Auxiliar (Docente Universitário)	Universidad de Ciego de Avila, Cuba

2012 - 2015	Professor Coordenador Convidado (Docente Ensino Superior Politécnico)	Universidade Katyavala Bwila, Angola

Outros

	Categoria Profissional Instituição de acolhimento	Empregador
2017 - 2019	COMPUTER SPECIALIST	JARDINES DEL REY INTERNATIONAL AIRPORT, Cuba

Projetos

Projeto

	Designação	Financiadores
2021 - Atual	TEXP@CT – Pacto de Inovação para a Digitalização do Têxtil e Vestuário 02/C05-i01.01/2022.PC644915249-00000025 Desenvolvimento técnico Centro de Computação Gráfica, Portugal
2021 - Atual	HfPT - Health from Portugal 02/C05-i01.01/2022.PC644937233-00000047 Desenvolvimento técnico Centro de Computação Gráfica, Portugal
2021 - Atual	Aliança para a Transição Energética 02/C05-i01.02/2022.PC644914747-00000023 Desenvolvimento técnico Centro de Computação Gráfica, Portugal
2020 - Atual	CHIC: Cooperative Holistic view on Internet and Content POCI-01-0247-FEDER-024498 Bolseiro de Investigação	Concluído
2021 - 2023	iPATH: Intelligent Network Center for Digital Pathology POCI-01-0247-FEDER-047069 Desenvolvimento técnico Centro de Computação Gráfica, Portugal	Concluído
2021 - 2023	IntVIS4Insp: Intelligent and Flexible Computer Vision System for Automatic Inspection POCI-01-0247-FEDER-042778 Desenvolvimento técnico Centro de Computação Gráfica, Portugal	Concluído
2020 - 2023	STVgoDigital: Digitalization of the Textile and Clothing Sector's value chain. POCI-01-0247-FEDER-046086 Desenvolvimento técnico Centro de Computação Gráfica, Portugal	Concluído
2020 - 2022	Intelligent 4D Moulds POCI-01-0247-FEDER-033625 Desenvolvimento técnico	Concluído

Produções

Publicações

Artigo em conferência	José Rubén Pozo Pérez; Yanelys Fernández Llerena; Yusbel Chávez Castilla; Edel Garcia Reyes; Luís Gonzaga Magalhães; Miguel Angel Guevara Lopez. "AOI for automotive industry - a quality assessment approach combining 2D and 3D sensors". 2024. 10.1145/3665318.3677169 João Oliveira; Alexandre Carrança; Eduardo Santos; Luís Evangelista; Rosane Sampaio; Joana Andrade; Yusbel Chávez Castilla; et al. "Towards remote rehabilitation with gaming, digital monitor and computer vision technologies". 2024. 10.1145/3665318.3677162
Artigo em revista	Pérez, José; laamr-León, Javier; Castilla, Yusbel; Shahrabadi, Somayeh; Anjos, Vitor; Adão, Telmo; Guevara-López, Miguel; et al. "A cloud-based 3D real-time inspection platform for industry". (2024): http://hdl.handle.net/10174/36940. https://doi.org/10.1016/j.procs.2023.01.298 Yusbel Chávez Castilla. "Fabric Hairiness Analysis for Quality Inspection of Pile Fabric Products Using Computer Vision Technology". Procedia Computer Science (2022): http://dx.doi.org/10.1016/j.procs.2022.08.072. 10.1016/j.procs.2022.08.072 Yusbel Chávez Castilla. "Leather Defect Detection Using Semantic Segmentation: A Hardware platform and software prototype". Procedia Computer Science (2022): http://dx.doi.org/10.1016/j.procs.2022.08.070. 10.1016/j.procs.2022.08.070 Yusbel Chávez Castilla. "Defect detection in the textile industry using image-based machine learning methods: a brief review". Journal of Physics: Conference Series 2224 1 (2022): 012010-012010. http://dx.doi.org/10.1088/1742-6596/2224/1/012010. 10.1088/1742-6596/2224/1/012010 Yusbel Chávez Castilla. "Using deep learning to detect the presence/absence of defects on leather: on the way to build an industry-driven approach". Journal of Physics: Conference Series 2224 1 (2022): 012009-012009. http://dx.doi.org/10.1088/1742-6596/2224/1/012009. 10.1088/1742-6596/2224/1/012009 Yusbel Chávez Castilla. "A Ubiquitous Service-Oriented Automatic Optical Inspection Platform for Textile Industry". Procedia Computer Science 196 (2022): 217-225. http://dx.doi.org/10.1016/j.procs.2021.12.008. 10.1016/j.procs.2021.12.008 Yusbel Chávez Castilla. "PANTSA Influence in grouping Mixed and Incomplete Data". International Journal of Innovative Technology and Exploring Engineering 9 2 (2019): 579-583. http://dx.doi.org/10.35940/ijitee.b6534.129219. 10.35940/ijitee.b6534.129219 Yusbel Chávez Castilla. "Clustering mixed data using an Artificial Bee Colony". International Journal of Innovative Technology and Exploring Engineering 9 2 (2019): 65-70. http://dx.doi.org/10.35940/ijitee.a4861.129219. 10.35940/ijitee.a4861.129219 Yusbel Chávez Castilla. "Clustering Techniques for Document Classification". Research in Computing Science (2016): https://rcs.cic.ipn.mx/2016_118/Clustering%20Techniques%20for%20Document%20Classification.pdf. DOI: 10.13053/rcs-118-1-11
Capítulo de livro	Dibet Garcia Gonzalez; João Carias; Yusbel Chávez Castilla; José Rodrigues; Telmo Adão; Rui Jesus; Luís Gonzaga Mendes Magalhães; et al. "Evaluating Rotation Invariant Strategies for Mitosis Detection Through YOLO Algorithms". 2023. 10.1007/978-3-031-32029-3_3
Livro	Yusbel Chávez Castilla. Segmentación de núcleos en imágenes de células cérvico uterinas.. Espanha. 2012.

Outros

Outra produção

A cloud-based 3D real-time inspection platform for industry: A casestudy focusing automotive cast iron parts. A 3D real-Time quality inspection platform that specifically focus on automotive cast iron parts was developed for the industry and is presented in this work. It is supported by a cloud-based platform, which combines recent software and hardware advances to deal with large amounts of information related to the acquisition process and the computational power needed to execute the computer vision pl. 2023. Pérez, José; León, Javier; Castilla, Yusbel; Shahrabadi, Somayeh; Anjos, Vitor; Adão, Telmo; López, Miguel Ángel Guevara; et al. https://hdl.handle.net/1822/88987.
10.1016/j.procs.2023.01.298
Evaluating rotation invariant strategies for mitosis detection through YOLO algorithms. First Online: 14 May 2023. Cancer diagnosis is of major importance in the field of human medical pathology, wherein a cell division process known as mitosis constitutes a relevant biological pattern analyzed by professional experts, who seek for such occurrence in presence and number through visual observation of microscopic imagery. This is a time-consuming and exhausting task that can benefit fr. 2023. Gonzalez, Dibet Garcia; Carias, João; Castilla, Yusbel Chávez; Rodrigues, José; Adão, Telmo; Jesus, Rui; Magalhães, Luís Gonzaga Mendes; et al. https://hdl.handle.net/1822/89117.
10.1007/978-3-031-32029-3_3
Defect detection in the textile industry using image-based machine learning methods: A brief review. Traditionally, computer vision solutions for detecting elements of interest (e.g., defects) are based on strict context-sensitive implementations to address contained problems with a set of well-defined conditions. On the other hand, several machine learning approaches have proven their generalization capacity, not only to improve classification continuously, but also to learn from new examples, b. 2022. Shahrabadi, Somayeh; Castilla, Yusbel; Guevara, Miguel; Magalhães, Luís Gonzaga Mendes; Gonzalez, Dibet; Adão, Telmo. https://hdl.handle.net/1822/89082.
10.1088/1742-6596/2224/1/012010
Leather defect detection using semantic segmentation: A hardware platform and software prototype. Leather is a textile material made from the animal skins created through a process of tanning of hides. It is a durable material, and the price is higher compared to other types of textiles. The leather is highly sensitive to its quality and surface defect condition as it is expensive. The manual defect inspection process is tedious, labor intensive, time consuming, and often prone to human error.. 2022. Khanal, Salik Ram; Silva, Jorge; Magalhães, Luís Gonzaga Mendes; Soares, João; Gonzalez, Dibet Garcia; Castilla, Yusbel Chavez; Ferreira, Manuel J.. https://hdl.handle.net/1822/89084.
10.1016/j.procs.2022.08.070
Using deep learning to detect the presence/absence of defects on leather: On the way to build an industry-driven approach. In textile/leather manufacturing environments, as in many other industrial contexts, quality inspection is an essential activity that is commonly performed by human operators. Error, fatigue, ergonomic issues, and related costs associated to this fashion of carrying out fabric validation are aspects concerning companies' strategists, whose mission includes to watch over the physical integrity of t. 2022. Adão, Telmo; Gonzalez, Dibet; Castilla, Yusbel Chavez; Pérez, José; Shahrabadi, Somayeh; Sousa, Nuno; Guevara, Miguel; Magalhães, Luís Gonzaga Mendes. https://hdl.handle.net/1822/89086.
10.1088/1742-6596/2224/1/012009
A ubiquitous service-oriented automatic optical inspection platform for textile industry. Within a highly competitive market context, quality standards are vital for the textile industry, in which related procedures to assess respective manufacture still mainly rely on human-based visual inspection. Thereby, factors such as ergonomics, analytical subjectivity, tiredness and error susceptibility affect the employee's performance and comfort in particular and impact the economic healthin. 2021. Gonzalez, Dibet Garcia; Castilla, Yusbel Chavez; Shaharadaby, Somayeh; Mackay, Ana Margarida; Soares, Lúcia; Guimarães, Pedro; Morais, Francisco; et al. https://hdl.handle.net/1822/82409.
10.1016/j.procs.2021.12.008