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ORCIDKha Cong Nguyen
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2020 – today
- 2023
[c8]Masayuki Honda, Hung Tuan Nguyen, Cuong Tuan Nguyen, Kha Cong Nguyen, Ryosuke Odate, Takashi Kanemaru, Masaki Nakagawa:
Incremental Teacher Model with Mixed Augmentations and Scheduled Pseudo-label Loss for Handwritten Text Recognition. ICDAR (4) 2023: 287-301- 2021
- [c7]Kha Cong Nguyen, Ryosuke Odate:
A High Accuracy Text Detection Model of Newly Constructing and Training Strategies. ICPRAM 2021: 635-642 - 2020
- [j4]Kha Cong Nguyen
, Cuong Tuan Nguyen, Masaki Nakagawa:
Nom document digitalization by deep convolution neural networks. Pattern Recognit. Lett. 133: 8-16 (2020) - [c6]Kha Cong Nguyen, Cuong Tuan Nguyen, Masaki Nakagawa:
A Semantic Segmentation-based Method for Handwritten Japanese Text Recognition. ICFHR 2020: 127-132
2010 – 2019
- 2019
- [j3]Nam Tuan Ly, Kha Cong Nguyen, Cuong Tuan Nguyen, Masaki Nakagawa:
Recognition of Anomalously Deformed Kana Sequences in Japanese Historical Documents. IEICE Trans. Inf. Syst. 102-D(8): 1554-1564 (2019) - [c5]Kha Cong Nguyen, Cuong Tuan Nguyen, Seiji Hotta, Masaki Nakagawa:
A Character Attention Generative Adversarial Network for Degraded Historical Document Restoration. ICDAR 2019: 420-425 - 2017
- [j2]Kha Cong Nguyen, Cuong Tuan Nguyen, Masaki Nakagawa:
A Segmentation Method of Single- and Multiple-Touching Characters in Offline Handwritten Japanese Text Recognition. IEICE Trans. Inf. Syst. 100-D(12): 2962-2972 (2017) - [c4]Nam Tuan Ly, Cuong Tuan Nguyen, Kha Cong Nguyen, Masaki Nakagawa:
Deep Convolutional Recurrent Network for Segmentation-Free Offline Handwritten Japanese Text Recognition. MOCR@ICDAR 2017: 5-9 - [c3]Hung Tuan Nguyen, Nam Tuan Ly, Kha Cong Nguyen, Cuong Tuan Nguyen, Masaki Nakagawa:
Attempts to recognize anomalously deformed Kana in Japanese historical documents. HIP@ICDAR 2017: 31-36 - [c2]Kha Cong Nguyen, Cuong Tuan Nguyen, Masaki Nakagawa:
Tens of Thousands of Nom Character Recognition by Deep Convolution Neural Networks. HIP@ICDAR 2017: 37-41 - 2016
- [j1]Truyen Van Phan, Kha Cong Nguyen, Masaki Nakagawa:
A Nom historical document recognition system for digital archiving. Int. J. Document Anal. Recognit. 19(1): 49-64 (2016) - [c1]Kha Cong Nguyen, Masaki Nakagawa:
Enhanced Character Segmentation for Format-Free Japanese Text Recognition. ICFHR 2016: 138-143
Coauthor Index
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