Victor Hugo C. de Albuquerque

Victor Hugo C. de Albuquerque has a PhD in Mechanical Engineering with emphasis on Materials from the Federal University of Paraíba (2010), an MSc in Teleinformatics Engineering from the Federal University of Ceará (2007), and he graduated in Mechatronics Technology at the Federal Center of Technological Education of Ceará (2006). He is currently Assistant VI Professor of the Graduate Program in Applied Informatics at the University of Fortaleza (UNIFOR). He has experience in Computer Systems, mainly in the research fields of: Applied Computing, Intelligent Systems, Visualization and Interaction, with specific interest in Pattern Recognition, Artificial Intelligence, Image Processing and Analysis, as well as Automation with respect to biological signal/image processing, image segmentation, biomedical circuits and human/brain-machine interaction, NeuroBiofeedback, Neurorehabilitation, Visual Stimulation, including Augmented and Virtual Reality Simulation Modeling for animals and humans. Additionally, he has research at the microstructural characterization field through the combination of non-destructive techniques with signal/image processing and analysis, and pattern recognition.

Publications

Novel AI Applications for Advancing Earth Sciences
Novel AI Applications for Advancing Earth Sciences
Sudesh Yadav, Satya Prakash Yadav, Pethuru Raj, Prabhakar Tiwari, Victor Hugo C. de Albuquerque. © 2024. 405 pages.
The Earth Sciences industry faces a new challenge - the need for accurate, efficient, and reliable methods to monitor and predict geological phenomena and environmental changes....
Principles and Methods of Explainable Artificial Intelligence in Healthcare
Principles and Methods of Explainable Artificial Intelligence in Healthcare
Victor Hugo C. de Albuquerque, P. Naga Srinivasu, Akash Kumar Bhoi, Alfonso González Briones. © 2022. 347 pages.
Explainable artificial intelligence is proficient in operating and analyzing the unconstrainted environment in fields like robotic medicine, robotic treatment, and robotic...
Deep Learning Strategies for Security Enhancement in Wireless Sensor Networks
Deep Learning Strategies for Security Enhancement in Wireless Sensor Networks
K. Martin Sagayam, Bharat Bhushan, A. Diana Andrushia, Victor Hugo C. de Albuquerque. © 2020. 405 pages.
Wireless sensor networks have gained significant attention industrially and academically due to their wide range of uses in various fields. Because of their vast amount of...