Web Access Research Portal

Researcher: Tran, SN (Dr Son Tran)

Fields of Research

Intelligent robotics
Natural language processing
Computer vision
Artificial intelligence
Applications in health
Ecological impacts of climate change and ecological adaptation
Rural and remote health services
Neural networks
Autonomous agents and multiagent systems
Aged health care
Deep learning
Mixed initiative and human-in-the-loop
Pattern recognition
Machine learning
Pervasive computing
Knowledge representation and reasoning

Research Objectives

Health related to ageing
Information systems, technologies and services
Artificial intelligence
Intelligence, surveillance and space
Ecosystem adaptation to climate change
Diagnosis of human diseases and conditions
Mental health services
Legal processes
Evaluation of health outcomes
Emerging defence technologies
Visual communication
The media
Learner and learning
Health education and promotion

Career Best Publications

Research Publications

Analysis of concept drift in fake reviews detection; Expert Systems with Applications
Data augmentation with generative adversarial networks for grocery product image recognition; 16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020
Deep learning for retail product recognition: challenges and techniques; Computational Intelligence and Neuroscience
dpUGC: Learn differentially private representation for user generated contents; 20th International Conference on Computational Linguistics and Intelligent Text Processing
ETNLP: A visual-aided systematic approach to select pre-trained embeddings for a downstream task; Recent Advances in Natural Language Processing International Conference
Fake reviews detection: A survey; IEEE Access
Generalising the discriminative restricted Boltzmann machines; 26th International Conference on Artificial Neural Networks: Artificial Neural Networks and Machine Learning
Hand tremor detection in videos with cluttered background using neural network based approaches; Health Information Science and Systems
Human identification via unsupervised feature learning from UWB radar data; 2018 Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2018): Advances in Knowledge Discovery and Data Mining
Improving multi-resident activity recognition for smarter homes; International Joint Conference on Artificial Intelligence - Workshop on AI for Internet of Things
Improving recurrent neural networks with predictive propagation for sequence labelling; 25th International Conference on Neural Information Processing (ICONIP 2018)
Mixed-dependency models for multi-resident activity recognition in smart homes; Multimedia Tools and Applications
Multi-resident activity monitoring in smart homes: a case study; 2018 IEEE International Conference on Pervasive Computing and Communications Workshops
Neural-symbolic computing: An effective methodology for principled integration of machine learning and reasoning; Journal of Applied Logics
Neural-symbolic probabilistic argumentation machines; 17th International Conference Principles of Knowledge Representation and Reasoning
On multi-resident activity recognition in ambient smart-homes; Artificial Intelligence Review
Probabilistic approaches for music similarity using restricted Boltzmann machines; Neural Computing and Applications
Sentimental Analysis for AIML-Based E-Health Conversational Agents; Neural Information Processing: ICONIP 2018
Sequence classification restricted Boltzmann machines with gated units; IEEE Transactions on Neural Networks and Learning Systems
Some algorithms to solve a bi-objectives problem for team selection; Applied Sciences
Speaker recognition with hybrid features from a deep belief network; Neural Computing and Applications
Towards Multi-resident Activity Monitoring with Smarter Safer Home Platform; Smart Assisted Living. Computer Communications and Networks
Unsupervised neural-symbolic integration; International Joint Conference on Artificial Intelligence - Workshop on Explainable AI

Research Projects

Research Candidate Supervision