15 citations · 15 across the 2 of their papers we have counts for
3 papers
Deep Reinforcement Learning Models Predict Visual Responses in the Brain: A Preliminary Result
Maytus Piriyajitakonkij, Sirawaj Itthipuripat, Theerawit Wilaiprasitporn +1
Supervised deep convolutional neural networks (DCNNs) are currently one of the best computational models that can explain how the primate ventral visual stream solves object recogn…
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…
An Explicit Local and Global Representation Disentanglement Framework with Applications in Deep Clustering and Unsupervised Object Detection
Rujikorn Charakorn, Yuttapong Thawornwattana, Sirawaj Itthipuripat +3
Visual data can be understood at different levels of granularity, where global features correspond to semantic-level information and local features correspond to texture patterns.…