Special Issue on Deep Learning for Intelligent Sensing,Decision-Making and Control
摘要截稿:
全文截稿: 2018-06-30
影响因子: 4.438
期刊难度:
CCF分类: C类
中科院JCR分区:
• 大类 : 计算机科学 - 2区
• 小类 : 计算机:人工智能 - 2区
Overview
Intelligent sensing, especially together with autonomous decision-making and control recently has gained wide attention, with successful showcases in different areas such as the autonomous flying droids, self-driving cars, and amazon kiva systems. One primary ultimate goal is that via active sensing, the computer/machine can learn through either supervised or unsupervised information to perform different tasks.
This fact renders learning a fundamental component for both sensing and control. Among many learning approaches, deep learning has obtained a series of success across various domains including image, speech, text as well as various user-interaction data. The resulting increased sensing capability opens up new possibility for more intelligent decision-making and control. On the other hand, emerging technology e.g. deep reinforcement learning and big data also spur the research for new control paradigm.
The continuously increasing interest in the intersection between intelligent sensing, big data, and deep learning motivates us to organize this special section to study the learning of feature representations for decision-making and control problems.
This special issue will feature original research papers related to (but limited to) learning theory, feature representation, and end-to-end automatic systems for intelligent sensing and control. The survey/vision/review papers are also welcome. The topics of interest include, but not limited to:
- New deep network structure/learning algorithm for intelligent sensing
- Multi-modal/task learning for decision-making and control
- Reinforcement deep learning
- Adversarial deep learning
- Online learning via deep network
- End-to-end learning system for sensing and control
- Visual simultaneous localization and mapping (VSLAM) by deep learning
- Statistical learning for mining and analysis of big data
- New regression/classification model for expert system