Sira Yongchareon

Associate Professor

University of Auckland

New Zealand

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About

Dr. Sira Yongchareon is an Associate Professor at Auckland University of Technology in New Zealand. Her research focuses on machine learning applications in various fields, including vital sign monitoring, financial forecasting, indoor localization, and mental health detection. She has published recent articles on advanced deep learning models and the integration of different neural network architectures for practical applications in technology and health.

Sira Yongchareon

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Articles (17)

A survey on machine learning approaches for vital sign monitoring using radar

AI-Driven Intelligent Financial Forecasting: A Comparative Study of Advanced Deep Learning Models for Long-Term Stock Market Prediction

Efficient Deep Learning-Based Device-Free Indoor Localization Using Passive Infrared Sensors

LLM-Augmented Linear Transformer–CNN for Enhanced Stock Price Prediction

An attention-based CNN-BiLSTM model for depression detection on social media text

A Real-Time Beam Steering and Accurate Vital Sign Estimation Method in an Indoor Environment

Human Vital Signs Estimation Using Resonance Sparse Spectrum Decomposition

On Fusing Artificial and Convolutional Neural Network Features for Automatic Bug Assignments

Motif-based graph attentional neural network for web service recommendation

Graph-based joint pandemic concern and relation extraction on Twitter

Transformer With Bidirectional GRU for Nonintrusive, Sensor-Based Activity Recognition in a Multiresident Environment

Deep CNN-LSTM Network for Indoor Location Estimation Using Analog Signals of Passive Infrared Sensors

Efficient privacy-preserving data replication in fog-enabled IoT

High-order autoencoder with data augmentation for collaborative filtering

Locally Weighted Ensemble-Detection-Based Adaptive Random Forest Classifier for Sensor-Based Online Activity Recognition for Multiple Residents

A Survey on Device-free Indoor Localization and Tracking in the Multi-resident Environment

Hybrid Fuzzy C-Means CPD-Based Segmentation for Improving Sensor-Based Multiresident Activity Recognition

Collaborators (6)

Md Saiful Islam

Jian Yu

Sajib Mistry

Saeed Ur Rehman

Edmund M-K Lai

Quan Bai

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