SPECIAL ISSUE ON UBIQUITOUS ARTIFICIAL INTELLIGENCE AND CAPSULE NETWORKS
摘要截稿:
全文截稿: 2019-02-10
影响因子: 2.663
期刊难度:
CCF分类: 无
中科院JCR分区:
• 大类 : 计算机科学 - 3区
• 小类 : 计算机:硬件 - 3区
• 小类 : 计算机:跨学科应用 - 3区
• 小类 : 工程:电子与电气 - 3区
Overview
Capsule networks will certainly transform the capabilities and possibilities of machine learning in many areas. They help machines understand images by giving them a new aspect, similar to the three-dimensional perspective that humans have. They require less training data and deliver equivariant mapping, promising for image segmentation and object detection. With the use of dynamic routing and reconstruction regularization, the capsule network model would be both rotation-invariant and spatially-aware, addressing its inherent limitations.
The rise of Artificial Intelligence has paved the way for ubiquitous computing, enabled machines to adapt and truly build intelligence to make smart decisions, amplify human creativity, complete high-precision operations, optimize costs, and much more. Increased computing power and sensor data along with improved AI algorithms are driving the trend towards machine learning. AI is a tool that is becoming so useful and ubiquitous that it will soon become a kind of sixth sense.
This special issue aims to gather the latest research and development achievements in recent trends in ubiquitous artificial intelligence and capsule networks, and to promote their applications in all important emerging research fields.
New research articles are solicited in the following areas:
- Capsule networks in deep learning
- Convolutional Neural networks in perceptron algorithm
- Artificial Intelligence systems and ubiquitous robotics
- Smart robots for multi-task performance
- High dimensional date routing in AI
- AI framework for smart network management
- Capsules in the brain networks
- Capsule implementation in the network
- Feed-forward neural networks
- Deep reinforcement algorithms
- Recurrent neural networks in AI
- Mobility management in recurrent neural networks