What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Computer network
His primary areas of investigation include Artificial intelligence, Real-time computing, Speech recognition, The Internet and Communications system.
His studies in Artificial intelligence integrate themes in fields like Data mining, Natural language processing, Computer vision, Machine learning and Pattern recognition.
His Real-time computing research includes themes of Scale, IVMS, Vehicle tracking system and Asset.
The Vehicle tracking system study combines topics in areas such as Simulation and Robustness.
His study on The Internet also encompasses disciplines like
- Bluetooth and related Computer network,
- Multimedia which intersects with area such as World Wide Web.
His study looks at the relationship between Communications system and topics such as Mobile device, which overlap with Computer hardware and Mobile computing.
His most cited work include:
- Engine fault diagnosis based on multi-sensor information fusion using Dempster-Shafer evidence theory (338 citations)
- Vehicle visual and non-visual data recording system (308 citations)
- Vehicle immersive communication system (279 citations)
What are the main themes of his work throughout his whole career to date?
Otman Basir focuses on Artificial intelligence, Computer vision, Machine learning, Fuzzy logic and Pattern recognition.
His Artificial intelligence study combines topics from a wide range of disciplines, such as Speech recognition, Data mining and Natural language processing.
The various areas that Otman Basir examines in his Computer vision study include Global Positioning System and Robustness.
Otman Basir carries out multidisciplinary research, doing studies in Machine learning and Evidential reasoning approach.
His Fuzzy set, Fuzzy classification and Fuzzy control system investigations are all subjects of Fuzzy logic research.
His Dempster–Shafer theory research extends to Sensor fusion, which is thematically connected.
He most often published in these fields:
- Artificial intelligence (37.39%)
- Computer vision (12.77%)
- Machine learning (9.42%)
What were the highlights of his more recent work (between 2014-2021)?
- Artificial intelligence (37.39%)
- Machine learning (9.42%)
- Distributed computing (8.51%)
In recent papers he was focusing on the following fields of study:
Otman Basir mainly investigates Artificial intelligence, Machine learning, Distributed computing, Operations research and Computer network.
The concepts of his Artificial intelligence study are interwoven with issues in Brain tumor, Computer vision and Pattern recognition.
In his research, Support vector machine is intimately related to Maximization, which falls under the overarching field of Pattern recognition.
Otman Basir interconnects Classifier and Medical diagnosis in the investigation of issues within Machine learning.
His Distributed computing research is multidisciplinary, incorporating perspectives in Wireless sensor network, Systems architecture and Job shop scheduling.
In general Computer network study, his work on Telecommunications network, Protocol and Node often relates to the realm of Service delivery framework, thereby connecting several areas of interest.
Between 2014 and 2021, his most popular works were:
- Semi-Flocking Algorithm for Motion Control of Mobile Sensors in Large-Scale Surveillance Systems (64 citations)
- An evaluation of classifier-specific filter measure performance for feature selection (50 citations)
- A Low-Cost Lane-Determination System Using GNSS/IMU Fusion and HMM-Based Multistage Map Matching (23 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Computer network
Otman Basir mainly focuses on Artificial intelligence, Automotive engineering, Energy consumption, Real-time computing and Embedded system.
His work carried out in the field of Artificial intelligence brings together such families of science as Machine learning and Map matching.
His Automotive engineering research includes elements of Battery, Energy and Simulation.
His Energy consumption research is multidisciplinary, relying on both Quality, Management control system, Resource allocation and Focus.
His work deals with themes such as Orientation, Calibration, Gyroscope and Fleet management, which intersect with Real-time computing.
His research in Embedded system intersects with topics in Management system, Survivability and Sensor node, Key distribution in wireless sensor networks, Mobile wireless sensor network.
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