Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive ...

While advances in artificial intelligence have been slow to reach commercial P&C insurance, new trends in data augmentation could help pick up the pace, according to experts on a recent Insurtech ...

New research from the Data Provenance Initiative has found a dramatic drop in content made available to the collections used to build artificial intelligence. By Kevin Roose Reporting from San ...

Introduction: In recent years, the use of EEG signals for seizure detection has gained widespread academic attention. Aiming at the problem of overfitting deep learning models due to the small number ...

This repository has a pytorch implementation of data augmentation for NER, introduced in our COLING 2020 paper: Xiang Dai and Heike Adel. 2020. An Analysis of Simple ...

NLP, or Natural Language Processing, is a field of AI focusing on human-computer interaction using language. Text analysis, translation, chatbots, and sentiment analysis are just some of its many ...

Introduction: Due to the lack of devices and the difficulty of gathering patients, the small sample size is one of the most challenging problems in functional brain network (FBN) analysis. Previous ...

Abstract: The accuracy obtained with deep learning-based systems usually depends on the availability of large image datasets, which is not always possible. Consequently, it is necessary to apply ...