What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Statistics
Héctor Pomares mostly deals with Artificial intelligence, Data mining, Machine learning, Activity recognition and Function approximation.
He interconnects Window, Interval and Time series in the investigation of issues within Artificial intelligence.
His Data mining study combines topics from a wide range of disciplines, such as Membership function, Fuzzy number, Fuzzy classification, Type-2 fuzzy sets and systems and Fuzzy set operations.
His biological study spans a wide range of topics, including Process and Pattern recognition.
His work in Activity recognition addresses subjects such as Computer vision, which are connected to disciplines such as Key and Benchmark.
His studies deal with areas such as Function and Radial basis function as well as Function approximation.
His most cited work include:
- Window Size Impact in Human Activity Recognition (248 citations)
- Multiobjective evolutionary optimization of the size, shape, and position parameters of radial basis function networks for function approximation (173 citations)
- mHealthDroid: A Novel Framework for Agile Development of Mobile Health Applications (170 citations)
What are the main themes of his work throughout his whole career to date?
Héctor Pomares mainly investigates Artificial intelligence, Fuzzy logic, Fuzzy control system, Algorithm and Artificial neural network.
His Artificial intelligence research is multidisciplinary, relying on both Machine learning, Data mining and Pattern recognition.
His research investigates the link between Fuzzy logic and topics such as Control theory that cross with problems in Process control and Control engineering.
He has included themes like Evolutionary algorithm, Benchmark, Function approximation and Time series in his Algorithm study.
His research investigates the connection between Artificial neural network and topics such as Genetic algorithm that intersect with issues in Crossover.
His Defuzzification research focuses on Neuro-fuzzy and how it relates to Fuzzy set operations.
He most often published in these fields:
- Artificial intelligence (35.86%)
- Fuzzy logic (22.78%)
- Fuzzy control system (21.52%)
What were the highlights of his more recent work (between 2013-2021)?
- Wearable computer (6.75%)
- Artificial intelligence (35.86%)
- Activity recognition (9.28%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Wearable computer, Artificial intelligence, Activity recognition, mHealth and Human–computer interaction.
The various areas that Héctor Pomares examines in his Wearable computer study include Domain, Simulation, Mobile device and Reduced cost.
His Artificial intelligence study incorporates themes from Machine learning, Interval, Computer vision and Pattern recognition.
In the field of Machine learning, his study on Decision tree and Support vector machine overlaps with subjects such as Set and Energy consumption.
His studies in Activity recognition integrate themes in fields like Segmentation, Process, Data mining, Window and Sensor fusion.
As a member of one scientific family, Héctor Pomares mostly works in the field of Fuzzy set, focusing on Algorithm and, on occasion, Defuzzification, Fuzzy set operations, Fuzzy classification and Fuzzy mathematics.
Between 2013 and 2021, his most popular works were:
- Window Size Impact in Human Activity Recognition (248 citations)
- mHealthDroid: A Novel Framework for Agile Development of Mobile Health Applications (170 citations)
- Design, implementation and validation of a novel open framework for agile development of mobile health applications. (116 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Statistics
His primary scientific interests are in Wearable computer, Artificial intelligence, Activity recognition, Data mining and Mobile device.
His work investigates the relationship between Wearable computer and topics such as Simulation that intersect with problems in Computer vision and Intelligent sensor.
His research investigates the link between Artificial intelligence and topics such as Interval that cross with problems in Fuzzy logic, Computational complexity theory and Pattern recognition.
Héctor Pomares has researched Activity recognition in several fields, including Window, Segmentation, Sensor fusion and Soft sensor.
His studies examine the connections between Data mining and genetics, as well as such issues in Machine learning, with regards to Set.
His Mobile device research is multidisciplinary, incorporating perspectives in Digital health, Human–computer interaction and Reduced cost.
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