What is he best known for?
The fields of study he is best known for:
- Computer network
- The Internet
- Artificial intelligence
Mooi Choo Chuah mainly investigates Computer network, Network packet, Base station, Telecommunications link and Wireless.
His research integrates issues of Wireless network and Distributed computing in his study of Computer network.
His research in Network packet intersects with topics in Database transaction, Private network, Denial-of-service attack, Multiplexing and Encapsulation.
Base station is closely attributed to Quality of service in his work.
His Telecommunications link research is multidisciplinary, relying on both Burstiness and Access control.
His study explores the link between Wireless and topics such as Real-time computing that cross with problems in Node, Heartbeat and Time series.
His most cited work include:
- Method for admitting new connections based on usage priorities in a multiple access system for communications networks (476 citations)
- Method for overload control in a multiple access system for communication networks (271 citations)
- Method for access control in a multiple access system for communications networks (269 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Computer network, Network packet, Distributed computing, Wireless network and Real-time computing.
His Computer network study combines topics from a wide range of disciplines, such as Wireless, Wireless ad hoc network and Communication channel.
His Network packet study introduces a deeper knowledge of Computer security.
Mooi Choo Chuah works mostly in the field of Distributed computing, limiting it down to topics relating to Delay-tolerant networking and, in certain cases, Packet switching and Mobile computing, as a part of the same area of interest.
In his study, which falls under the umbrella issue of UMTS frequency bands, Quality of service is strongly linked to Radio access network.
His Base station research is multidisciplinary, incorporating elements of Frame, Terminal, Telecommunications link and Access control.
He most often published in these fields:
- Computer network (59.72%)
- Network packet (19.91%)
- Distributed computing (15.74%)
What were the highlights of his more recent work (between 2014-2021)?
- Artificial intelligence (11.57%)
- Deep learning (4.63%)
- Real-time computing (12.04%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Artificial intelligence, Deep learning, Real-time computing, Feature extraction and Machine learning.
As a member of one scientific family, Mooi Choo Chuah mostly works in the field of Artificial intelligence, focusing on Pattern recognition and, on occasion, Frame, Ground truth, Ranking and Image retrieval.
His studies deal with areas such as Exploit, Convolutional neural network and Spoofing attack as well as Feature extraction.
His work in the fields of Machine learning, such as Recurrent neural network, intersects with other areas such as Block.
He undertakes interdisciplinary study in the fields of Electronic signature and Computer network through his research.
As part of one scientific family, Mooi Choo Chuah deals mainly with the area of Computer network, narrowing it down to issues related to the Critical infrastructure, and often Smart grid.
Between 2014 and 2021, his most popular works were:
- DeepCham: Collaborative Edge-Mediated Adaptive Deep Learning for Mobile Object Recognition (59 citations)
- User Verification Leveraging Gait Recognition for Smartphone Enabled Mobile Healthcare Systems (58 citations)
- SBGAR: Semantics Based Group Activity Recognition (49 citations)
In his most recent research, the most cited papers focused on:
- Computer network
- The Internet
- Artificial intelligence
Mooi Choo Chuah mostly deals with Artificial intelligence, Real-time computing, Feature extraction, Deep learning and Software deployment.
When carried out as part of a general Artificial intelligence research project, his work on Representation is frequently linked to work in Clique and Charm, therefore connecting diverse disciplines of study.
His studies in Feature extraction integrate themes in fields like Visual Word, Frame, Activity recognition and Automatic image annotation.
His Deep learning research includes elements of Industrial control system and Convolutional neural network.
Along with Electronic signature, other disciplines of study including Mobile device and Computer network are integrated into his research.
Network packet and Communications protocol are the core of his Computer network study.
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