63 citations · 142 across the 8 of their papers we have counts for
8 papers
Clustering and Data Augmentation to Improve Accuracy of Sleep Assessment and Sleep Individuality Analysis
Shintaro Tamai, Masayuki Numao, Ken-ichi Fukui
Recently, growing health awareness, novel methods allow individuals to monitor sleep at home. Utilizing sleep sounds offers advantages over conventional methods like smartwatches,…
Adaptive Uncertainty-Guided Model Selection for Data-Driven PDE Discovery
Pongpisit Thanasutives, Takashi Morita, Masayuki Numao +1
We propose a new parameter-adaptive uncertainty-penalized Bayesian information criterion (UBIC) to prioritize the parsimonious partial differential equation (PDE) that sufficiently…
Noise-aware Physics-informed Machine Learning for Robust PDE Discovery
Pongpisit Thanasutives, Takashi Morita, Masayuki Numao +1
This work is concerned with discovering the governing partial differential equation (PDE) of a physical system. Existing methods have demonstrated the PDE identification from finit…
Adversarial Multi-task Learning Enhanced Physics-informed Neural Networks for Solving Partial Differential Equations
Pongpisit Thanasutives, Masayuki Numao, Ken-ichi Fukui
Recently, researchers have utilized neural networks to accurately solve partial differential equations (PDEs), enabling the mesh-free method for scientific computation. Unfortunate…
Encoder-Decoder Based Convolutional Neural Networks with Multi-Scale-Aware Modules for Crowd Counting
Pongpisit Thanasutives, Ken-ichi Fukui, Masayuki Numao +1
In this paper, we propose two modified neural networks based on dual path multi-scale fusion networks (SFANet) and SegNet for accurate and efficient crowd counting. Inspired by SFA…
Spatiotemporal Emotion Recognition using Deep CNN Based on EEG during Music Listening
Panayu Keelawat, Nattapong Thammasan, Masayuki Numao +1
Emotion recognition based on EEG has become an active research area. As one of the machine learning models, CNN has been utilized to solve diverse problems including issues in this…
Efficient Decision Trees for Multi-class Support Vector Machines Using Entropy and Generalization Error Estimation
Pittipol Kantavat, Boonserm Kijsirikul, Patoomsiri Songsiri +2
We propose new methods for Support Vector Machines (SVMs) using tree architecture for multi-class classi- fication. In each node of the tree, we select an appropriate binary classi…
Fusion of EEG and Musical Features in Continuous Music-emotion Recognition
Nattapong Thammasan, Ken-ichi Fukui, Masayuki Numao
Emotion estimation in music listening is confronting challenges to capture the emotion variation of listeners. Recent years have witnessed attempts to exploit multimodality fusing…