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期刊：Multimedia Tools and Applications

專刊：Special Issue on Soft Computing Techniques and Applications on Multimedia Data Analyzing Systems

領(lǐng)域：計(jì)算機(jī)圖形學(xué)與多媒體

難度：★★★

CCF分類：C類

影響因子：1.331

全文截稿：2017-09-20

網(wǎng)址：http://www.springer.com/journal/11042/about

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In computer science and engineering research, soft computing is the use of inexact solutions to computationally hard tasks such as the solution of NP-complete problems, for which there is no known algorithm that can compute an exact solution in polynomial time. Soft computing differs from conventional computing in that, unlike hard computing, it is tolerant of imprecision, uncertainty, partial truth, and approximation. In effect, the role model for soft computing is the human mind. The three major components of soft computing are fuzzy logic, neural network, and probabilistic reasoning, which complement each other. Fuzzy logic is used for error analysis and neural network for knowledge learning. Probabilistic reasoning is used to solve uncertainties and chestnut problems. It is concluded that fuzzy logic can simulate the function of human processing language, and neural network and probability inference model imitate human process data, knowledge learning and reasoning process, so it can deal with multivariable and nonlinear system problem with soft computing theory. The integration of soft computing and multimedia systems is the trend especially when the deep learning arises.

The aim of this special issue is to provide a premier international platform for wide range of professions including scholars, researchers, academicians and industry researchers to discuss and present the different types of cutting-edge soft computing techniques toward multimedia data analyzing systems. The special issue is open to submit novel and high quality research contributions. We target the researchers from both the industry and academia and anticipate that this special issue will open new entrance for further research and technology improvements in this important area.

Preferred topics in this issue include (but are not limited to):

- Online multimedia stream classification

- On-line single-pass active learning from multimedia data streams

- Multimedia big data mining, advanced analytics and visualization

- Operating systems and real-time processing for multimedia data-intensive applications

- Reliability in multimedia model predictions and parameters

- Dynamic dimension reduction and feature selection in multimedia streams

- User activities recognition for multimedia systems

- Semi-supervised learning from multimedia data streams

- Interplay between multimedia components for novel big data applications

- Soft computing model for multimedia assisted prediction

- Performance characterization, evaluation, optimization and design trade-offs

- MapReduce and parallel models for multimedia big data processing

- Web applications for multimedia systems

- Compiler support for multimedia data-intensive in high performance systems

- Multimedia information retrieval and feature extraction

- Remote sensing multimedia system model and platform

- Multimedia data stream modelling and identification

- Robotics, intelligent system and advanced manufacturing with multimedia

- Deep learning model and the applications in multimedia systems