His primary areas of study are Artificial intelligence, Computer vision, Segmentation, Computer security and Motion. His Artificial intelligence research incorporates themes from Computation, Cognition and Acute stress. Much of his study explores Computer vision relationship to International Affective Picture System.
The study incorporates disciplines such as Image processing, Image, Thresholding, Motion analysis and Fuzzy logic in addition to Segmentation. His Computer security study incorporates themes from Scheduling, Interface and Robustness. As part of the same scientific family, Antonio Fernández-Caballero usually focuses on Motion, concentrating on Sequence and intersecting with Set and Visual surveillance.
Antonio Fernández-Caballero focuses on Artificial intelligence, Computer vision, Human–computer interaction, Segmentation and Multi-agent system. His research investigates the connection between Artificial intelligence and topics such as Computation that intersect with problems in Lateral inhibition. His research related to Image, Pixel, Object, Image processing and Feature extraction might be considered part of Computer vision.
Antonio Fernández-Caballero combines topics linked to User interface with his work on Human–computer interaction. His Multi-agent system research includes themes of Intelligent agent and Software engineering. His research brings together the fields of Artificial neural network and Motion detection.
Antonio Fernández-Caballero spends much of his time researching Human–computer interaction, Artificial intelligence, Virtual reality, Social cognition and Electroencephalography. Antonio Fernández-Caballero interconnects Industry 4.0 and Gesture recognition in the investigation of issues within Human–computer interaction. His research integrates issues of Computer vision and Pattern recognition in his study of Artificial intelligence.
His work deals with themes such as Generator and Complex system, which intersect with Computer vision. His Social cognition research also works with subjects such as
Antonio Fernández-Caballero mostly deals with Artificial intelligence, Electroencephalography, Clinical psychology, Pattern recognition and Social cognition. Antonio Fernández-Caballero has researched Artificial intelligence in several fields, including Data science, Computer vision and Big data. His studies deal with areas such as Stimulus, Emotion recognition, Speech recognition and Nonlinear system, Nonlinear methods as well as Electroencephalography.
His work on Mood induction as part of his general Clinical psychology study is frequently connected to PsycINFO, Psychological intervention and Wellness promotion, thereby bridging the divide between different branches of science. His Pattern recognition research is multidisciplinary, relying on both Distress and Identification. The concepts of his Social cognition study are interwoven with issues in Domain, Affect and Quality of life.
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A survey of video datasets for human action and activity recognition
Jose M. Chaquet;Enrique J. Carmona;Antonio Fernández-Caballero.
Computer Vision and Image Understanding (2013)
Finding out general tendencies in speckle noise reduction in ultrasound images
Juan L. Mateo;Antonio Fernández-Caballero.
Expert Systems With Applications (2009)
Optical flow or image subtraction in human detection from infrared camera on mobile robot
Antonio Fernández-Caballero;José Carlos Castillo;Javier Martínez-Cantos;Rafael Martínez-Tomás.
Robotics and Autonomous Systems (2010)
Development of intelligent multisensor surveillance systems with agents
Juan Pavón;Jorge Gómez-Sanz;Antonio Fernández-Caballero;Julián J. Valencia-Jiménez.
Robotics and Autonomous Systems (2007)
Electrodermal Activity Sensor for Classification of Calm/Distress Condition
Roberto Zangróniz;Arturo Martínez-Rodrigo;José Manuel Pastor;María T. López.
Multimodal behavioral analysis for non-invasive stress detection
Davide Carneiro;José Carlos Castillo;Paulo Novais;Antonio FernáNdez-Caballero.
Expert Systems With Applications (2012)
Towards personalized recommendation by two-step modified Apriori data mining algorithm
Enrique Lazcorreta;Federico Botella;Antonio Fernández-Caballero.
Expert Systems With Applications (2008)
Smart environment architecture for emotion detection and regulation.
Antonio Fernández-Caballero;Arturo Martínez-Rodrigo;José Manuel Pastor;José Carlos Castillo.
Journal of Biomedical Informatics (2016)
Model-driven engineering techniques for the development of multi-agent systems
José M. Gascueña;Elena Navarro;Antonio Fernández-Caballero.
Engineering Applications of Artificial Intelligence (2012)
Sensor-driven agenda for intelligent home care of the elderly
íNgelo Costa;José Carlos Castillo;Paulo Novais;Antonio FernáNdez-Caballero.
Expert Systems With Applications (2012)
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