Model-driven deep-learning

• 来源期刊: 国家科学评论（英文版）
• 年，卷（期）: 2018,（1）
• 页码范围: 22-24
• 页数: 3页
• 语种: 英文
• DOI: 10.1093/nsr/nwx099

摘要

Deep learning has been widely recognized as the representative advances of machine learning or artificial intelligence in general nowadays [1,2].This can be attributed to the recent breakthroughs made by deep learning on a series of challenging applications.A deep-learning approach improves the accuracy rate of face recognition to be higher than 99％,beating the human level [3].For speech recognition and machine translation,deep learning is approaching the performance level of a simultaneous interpreter [4].For the game of ‘go',it successfully beats the human world champion [5].For diagnosis of some specific diseases,it has matched the level of medium or senior professional physicians [6].Until now,it has been hard to find areas in which the deep-learning technique has not been tried in their respective tasks.