Advanced Application of Machine Learning and Meta-Learning in Image and Text Analysis

Dear Colleagues,

Machine learning is a key field of artificial intelligence and plays an important role in various image and text analysis tasks such as object recognition, motion detection, medical scan analysis, sentiment analysis, information retrieval, document clustering, image captioning, text to image generation, etc.

Unlike the existing method of applying a fixed learning algorithm to a specific task, meta-learning, learning to learn, aims to improve the learning algorithm itself based on the experience of multiple learning tasks, thereby improving the performance of learning in a task that is given only a small amount of data.

This special issue focuses on the application of machine learning for image and text analysis, and meta-learning algorithms and applications for tasks that have limitations in applying machine learning due to the limited amount of available data. The topics of interest include but are not limited to:

• Machine Learning and Meta-Learning Theory
• Machine Learning for Image and Text Analysis
• Multi-Modal Machine Learning and Meta-Learning
• Meta-Learning for Computer Vision Tasks
• Meta-Learning for Natural Language Processing
• Meta-Learning in Reinforcement Learning
• Unsupervised and Self-supervised Meta-Learning
• Practical Application of Meta-Learning

Prof. Juntae Kim
Prof. Nam Ik Cho
Prof. Changwon Lim
Guest Editors

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