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2020 – today
- 2025
[j4]Akara Supratak, Watsaporn Pornwatanacharoen, Varit Rungbanapan, Skonlawut Tasnaworanun, Rachata Chopdamrongtham, Thanapon Noraset, Manachaya Prukajorn, Pimkwan Jaru-ampornpan:
Dynamic blinking feature extraction for automated facial nerve paralysis detection. Comput. Biol. Medicine 187: 109722 (2025)- 2024
- [j3]Pisol Ruenin, Morakot Choetkiertikul, Akara Supratak
, Suppawong Tuarob:
TeReKG: A temporal collaborative knowledge graph framework for software team recommendation. Knowl. Based Syst. 289: 111492 (2024) - 2023
- [j2]Akara Supratak, Peter Haddawy:
Quantifying the impact of data characteristics on the transferability of sleep stage scoring models. Artif. Intell. Medicine 139: 102540 (2023) - [j1]Myat Su Yin, Peter Haddawy, Tim Ziemer, Fabian Wetjen, Akara Supratak, Kanrawee Chiamsakul, Worameth Siritanakorn, Tharit Chantanalertvilai, Patchara Sriwichai, Chaitawat Sa-ngamuang:
A deep learning-based pipeline for mosquito detection and classification from wingbeat sounds. Multim. Tools Appl. 82(4): 5189-5205 (2023) - [i3]Akara Supratak, Peter Haddawy:
Quantifying the Impact of Data Characteristics on the Transferability of Sleep Stage Scoring Models. CoRR abs/2304.06033 (2023) - 2022
- [c8]Kosin Saramas, Jidapa Kraisangka, Akara Supratak, Thanapon Noraset, Boonsit Yimwadsana, Worapan Kusakunniran:
HUMAN DETECTION AND SOCIAL DISTANCING MEASUREMENT IN A VIDEO. JCSSE 2022: 1-4 - 2021
- [c7]Myat Su Yin, Peter Haddawy, Borvorntat Nirandmongkol, Tup Kongthaworn, Chanaporn Chaisumritchoke, Akara Supratak, Chaitawat Sa-ngamuang, Patchara Sriwichai:
A Lightweight Deep Learning Approach to Mosquito Classification from Wingbeat Sounds. GoodIT 2021: 37-42 - 2020
- [c6]Akara Supratak, Yike Guo:
TinySleepNet: An Efficient Deep Learning Model for Sleep Stage Scoring based on Raw Single-Channel EEG. EMBC 2020: 641-644 - [c5]Myat Su Yin, Peter Haddawy, Benedikt Hosp, Paphon Sa-Ngasoongsong, Thanwarat Tanprathumwong, Madereen Sayo, Supawit Yangyuenpradorn, Akara Supratak:
A Study of Expert/Novice Perception in Arthroscopic Shoulder Surgery. ICMHI 2020: 71-77
2010 – 2019
- 2019
- [c4]Thanyaporn Noiplab, Mongkon Sakdanupab, Akara Supratak, Thanapong Intharah:
Construction of A Mobile Video Retrieval Dataset in the Cloud: Dos, Don'ts, and the Analysis. ISCIT 2019: 470-475 - 2017
- [b1]Akara Supratak:
Learning from biosignals. Imperial College London, UK, 2017 - [c3]Hao Dong, Akara Supratak, Luo Mai, Fangde Liu, Axel Oehmichen, Simiao Yu, Yike Guo:
TensorLayer: A Versatile Library for Efficient Deep Learning Development. ACM Multimedia 2017: 1201-1204 - [i2]Hao Dong, Akara Supratak, Luo Mai, Fangde Liu, Axel Oehmichen, Simiao Yu, Yike Guo:
TensorLayer: A Versatile Library for Efficient Deep Learning Development. CoRR abs/1707.08551 (2017) - 2016
- [p1]Akara Supratak, Chao Wu, Hao Dong, Kai Sun, Yike Guo:
Survey on Feature Extraction and Applications of Biosignals. Machine Learning for Health Informatics 2016: 161-182 - [i1]Hao Dong, Akara Supratak, Wei Pan, Chao Wu, Paul M. Matthews, Yike Guo:
Mixed Neural Network Approach for Temporal Sleep Stage Classification. CoRR abs/1610.06421 (2016) - 2014
- [c2]Yang Li, Li Guo, Akara Supratak, Yike Guo:
Enabling Performance as a Service for a Cloud Storage System. IEEE CLOUD 2014: 554-561 - [c1]Akara Supratak, Ling Li, Yike Guo:
Feature extraction with stacked autoencoders for epileptic seizure detection. EMBC 2014: 4184-4187
Coauthor Index
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