no code implementations • 23 Apr 2024 • Pongpisit Thanasutives, Ken-ichi Fukui
The result indicates that the asymptotic property of the UBIC and BIC holds indifferently.
no code implementations • 16 Apr 2024 • Shintaro Tamai, Masayuki Numao, Ken-ichi Fukui
Recently, growing health awareness, novel methods allow individuals to monitor sleep at home.
1 code implementation • 20 Aug 2023 • Pongpisit Thanasutives, Takashi Morita, Masayuki Numao, Ken-ichi Fukui
We propose a new parameter-adaptive uncertainty-penalized Bayesian information criterion (UBIC) to prioritize the parsimonious partial differential equation (PDE) that sufficiently governs noisy spatial-temporal observed data with few reliable terms.
1 code implementation • 26 Jun 2022 • Pongpisit Thanasutives, Takashi Morita, Masayuki Numao, Ken-ichi Fukui
This work is concerned with discovering the governing partial differential equation (PDE) of a physical system.
2 code implementations • 29 Apr 2021 • 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.
1 code implementation • arXiv.org 2020 • Pongpisit Thanasutives, Ken-ichi Fukui, Masayuki Numao, Boonserm Kijsirikul
In this paper, we proposed two modified neural network architectures based on SFANet and SegNet respectively for accurate and efficient crowd counting.
2 code implementations • 12 Mar 2020 • Pongpisit Thanasutives, Ken-ichi Fukui, Masayuki Numao, Boonserm Kijsirikul
Inspired by SFANet, the first model, which is named M-SFANet, is attached with atrous spatial pyramid pooling (ASPP) and context-aware module (CAN).
Ranked #1 on Crowd Counting on UCF CC 50
no code implementations • 28 Aug 2017 • Pittipol Kantavat, Boonserm Kijsirikul, Patoomsiri Songsiri, Ken-ichi Fukui, Masayuki Numao
We propose new methods for Support Vector Machines (SVMs) using tree architecture for multi-class classi- fication.
no code implementations • 30 Nov 2016 • Nattapong Thammasan, Ken-ichi Fukui, Masayuki Numao
Emotion estimation in music listening is confronting challenges to capture the emotion variation of listeners.