A survey on machine learning from few samples
نویسندگان
چکیده
The capability of learning and generalizing from very few samples successfully is a noticeable demarcation separating artificial intelligence human intelligence. Despite the long history dated back to early 2000s widespread attention in recent years with booming deep learning, surveys for sample (FSL) are available. We extensively study almost all papers FSL spanning now provide timely comprehensive survey FSL. In this survey, we review evolution current progress on FSL, categorize approaches into generative model based discriminative kinds principle, emphasize particularly meta approaches. also summarize several recently emerging extensional topics their latest advances. Furthermore, highlight important applications covering many research hotspots computer vision, natural language processing, audio speech, reinforcement robotic, data analysis, etc. Finally, conclude discussion promising trends hope providing guidance insights follow-up researches.
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ژورنال
عنوان ژورنال: Pattern Recognition
سال: 2023
ISSN: ['1873-5142', '0031-3203']
DOI: https://doi.org/10.1016/j.patcog.2023.109480