7 papers
High resolution weakly supervised localization architectures for medical images
Konpat Preechakul, Sira Sriswasdi, Boonserm Kijsirikul +1
In medical imaging, Class-Activation Map (CAM) serves as the main explainability tool by pointing to the region of interest. Since the localization accuracy from CAM is constrained…
MetaSleepLearner: A Pilot Study on Fast Adaptation of Bio-signals-Based Sleep Stage Classifier to New Individual Subject Using Meta-Learning
Nannapas Banluesombatkul, Pichayoot Ouppaphan, Pitshaporn Leelaarporn +8
Identifying bio-signals based-sleep stages requires time-consuming and tedious labor of skilled clinicians. Deep learning approaches have been introduced in order to challenge the…
Semi-supervised Thai Sentence Segmentation Using Local and Distant Word Representations
Chanatip Saetia, Ekapol Chuangsuwanich, Tawunrat Chalothorn +1
A sentence is typically treated as the minimal syntactic unit used for extracting valuable information from a longer piece of text. However, in written Thai, there are no explicit…
Towards Asynchronous Motor Imagery-Based Brain-Computer Interfaces: a joint training scheme using deep learning
Patcharin Cheng, Phairot Autthasan, Boriwat Pijarana +2
In this paper, the deep learning (DL) approach is applied to a joint training scheme for asynchronous motor imagery-based Brain-Computer Interface (BCI). The proposed DL approach i…
Universal Joint Feature Extraction for P300 EEG Classification using Multi-task Autoencoder
Apiwat Ditthapron, Nannapas Banluesombatkul, Sombat Ketrat +2
The process of recording Electroencephalography (EEG) signals is onerous and requires massive storage to store signals at an applicable frequency rate. In this work, we propose the…
Affective EEG-Based Person Identification Using the Deep Learning Approach
Theerawit Wilaiprasitporn, Apiwat Ditthapron, Karis Matchaparn +3
Electroencephalography (EEG) is another mode for performing Person Identification (PI). Due to the nature of the EEG signals, EEG-based PI is typically done while the person is per…