63 citations · 137 across the 14 of their papers we have counts for
9 papers · 1 filter
Coronavirus disease situation analysis and prediction using machine learning: a study on Bangladeshi population
Al-Akhir Nayan, Boonserm Kijsirikul, Yuji Iwahori
During a pandemic, early prognostication of patient infected rates can reduce the death by ensuring treatment facility and proper resource allocation. In recent months, the number…
CProp: Adaptive Learning Rate Scaling from Past Gradient Conformity
Konpat Preechakul, Boonserm Kijsirikul
Most optimizers including stochastic gradient descent (SGD) and its adaptive gradient derivatives face the same problem where an effective learning rate during the training is vast…
A Comparative Study of Pretrained Language Models on Thai Social Text Categorization
Thanapapas Horsuwan, Kasidis Kanwatchara, Peerapon Vateekul +1
The ever-growing volume of data of user-generated content on social media provides a nearly unlimited corpus of unlabeled data even in languages where resources are scarce. In this…
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…
Sub-Classifier Construction for Error Correcting Output Code Using Minimum Weight Perfect Matching
Patoomsiri Songsiri, Thimaporn Phetkaew, Ryutaro Ichise +1
Multi-class classification is mandatory for real world problems and one of promising techniques for multi-class classification is Error Correcting Output Code. We propose a method…