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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.
Identification

Personal identification

Full name
Yusbel Chávez Castilla

Citation names

  • Castilla, Yusbel

Author identifiers

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

Knowledge fields

  • Exact Sciences - Computer and Information Sciences

Languages

Language Speaking Reading Writing Listening Peer-review
Spanish; Castilian (Mother tongue)
English Intermediate (B1) Intermediate (B1) Intermediate (B1) Intermediate (B1) Intermediate (B1)
Portuguese Upper intermediate (B2) Upper intermediate (B2) Upper intermediate (B2) Upper intermediate (B2) Upper intermediate (B2)
Education
Degree Classification
2011
Concluded
Maestría en Informática Aplicada (Master)
Universidad de Ciego de Avila, Cuba
2009
Concluded
Ingeniería Informática (Licence)
Major in Informática
Universidad de Ciego de Avila, Cuba
Affiliation

Science

Category
Host institution
Employer
2019 - 2024 Contracted Researcher (Research) Centro de Computação Gráfica, Portugal
2019 - 2019 Research Trainee (Research) Centro de Computação Gráfica, Portugal

Teaching in Higher Education

Category
Host institution
Employer
2009 - 2017 Assistant Professor (University Teacher) Universidad de Ciego de Avila, Cuba
2012 - 2015 Invited Teacher Coordinator (Polytechnic Teacher) Universidade Katyavala Bwila, Angola

Others

Category
Host institution
Employer
2017 - 2019 COMPUTER SPECIALIST JARDINES DEL REY INTERNATIONAL AIRPORT, Cuba
Projects

Contract

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

Publications

Book
  1. Yusbel Chávez Castilla. Segmentación de núcleos en imágenes de células cérvico uterinas.. Spain. 2012.
Book chapter
  1. 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
Conference paper
  1. 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
  2. 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
Journal article
  1. 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
  2. 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
  3. 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
  4. 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
  5. 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
  6. 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
  7. 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
  8. 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
  9. 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

Other

Other output
  1. 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
  2. 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
  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
  4. 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
  5. 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
  6. 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