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Context-aware Stand-alone Neural Spelling Correction
XiangciLi, HairongLiu, LiangHuang....
Published date-11/12/2020
LanguageModelling, SpellingCorrection
Existing natural language processing systems are vulnerable to noisy inputs resulting from misspellings. On the contrary, humans can easily infer the corresponding correct words from their misspellings and surrounding context. …
Reinforcement Learning with Videos: Combining Offline Observations with Interaction
KarlSchmeckpeper, OlehRybkin, KostasDaniilidis....
Published date-11/12/2020
Reinforcement learning is a powerful framework for robots to acquire skills from experience, but often requires a substantial amount of online data collection. As a result, it is difficult to …
Neural network for estimation of optical characteristics of optically active and turbid scattering media
AliAlavi....
Published date-11/12/2020
One native source of quality deterioration in medical imaging, and especially in our case optical coherence tomography (OCT), is the turbid biological media in which photon does not take a …
Learning Inter-Modal Correspondence and Phenotypes from Multi-Modal Electronic Health Records
KejingYin, WilliamK.Cheung, BenjaminC.M.Fung....
Published date-11/12/2020
ComputationalPhenotyping
Non-negative tensor factorization has been shown a practical solution to automatically discover phenotypes from the electronic health records (EHR) with minimal human supervision. Such methods generally require an input tensor …
SVAM: Saliency-guided Visual Attention Modeling by Autonomous Underwater Robots
MdJahidulIslam, RuobingWang, KarindeLangis....
Published date-11/12/2020
ObjectDetection, SaliencyPrediction, SalientObjectDetection
This paper presents a holistic approach to saliency-guided visual attention modeling (SVAM) for use by autonomous underwater robots. Our proposed model, named SVAM-Net, integrates deep visual features at various scales …
Atrial Fibrillation Detection and ECG Classification based on CNN-BiLSTM
JiachengWang, WeihengLi....
Published date-11/12/2020
AtrialFibrillationDetection, ECGClassification
It is challenging to visually detect heart disease from the electrocardiographic (ECG) signals. Implementing an automated ECG signal detection system can help diagnosis arrhythmia in order to improve the accuracy …