858 citations
- Samsung (South Korea)KR8 papers
- Samsung Medical CenterKR2 papers
- Australian Centre for Robotic VisionAU1 paper
- Beijing Academy of Artificial IntelligenceCN1 paper
- Beijing University of Chemical TechnologyCN1 paper
- Chinese University of Hong KongHK1 paper
- Christian Doppler Laboratory for ThermoelectricityAT1 paper
- City College of New YorkUS1 paper
- Gachon UniversityKR1 paper
- Healthcare Technology Innovation CentreIN1 paper
- Inception Institute of Artificial IntelligenceAE1 paper
- Indian Institute of Technology MadrasIN1 paper
6 papers
Enhancing Semantic Understanding with Self-supervised Methods for Abstractive Dialogue Summarization
Hyunjae Lee, Jaewoong Yun, Hyunjin Choi +2
Contextualized word embeddings can lead to state-of-the-art performances in natural language understanding. Recently, a pre-trained deep contextualized text encoder such as BERT ha…
DUET: Detection Utilizing Enhancement for Text in Scanned or Captured Documents
Eun-Soo Jung, HyeongGwan Son, Kyusam Oh +3
We present a novel deep neural model for text detection in document images. For robust text detection in noisy scanned documents, the advantages of multi-task learning are adopted…
KoreALBERT: Pretraining a Lite BERT Model for Korean Language Understanding
Hyunjae Lee, Jaewoong Yoon, Bonggyu Hwang +3
A Lite BERT (ALBERT) has been introduced to scale up deep bidirectional representation learning for natural languages. Due to the lack of pretrained ALBERT models for Korean langua…
Analyzing Zero-shot Cross-lingual Transfer in Supervised NLP Tasks
Hyunjin Choi, Judong Kim, Seongho Joe +2
In zero-shot cross-lingual transfer, a supervised NLP task trained on a corpus in one language is directly applicable to another language without any additional training. A source…
Evaluation of BERT and ALBERT Sentence Embedding Performance on Downstream NLP Tasks
Hyunjin Choi, Judong Kim, Seongho Joe +1
Contextualized representations from a pre-trained language model are central to achieve a high performance on downstream NLP task. The pre-trained BERT and A Lite BERT (ALBERT) mod…
REFUGE Challenge: A Unified Framework for Evaluating Automated Methods for Glaucoma Assessment from Fundus Photographs
José Ignacio Orlando, Huazhu Fu, João Barbossa Breda +28
Glaucoma is one of the leading causes of irreversible but preventable blindness in working age populations. Color fundus photography (CFP) is the most cost-effective imaging modali…