Machine Learning in Computer Engineering Applications

Dear Colleagues,

Machine learning is a dynamically developing branch of artificial intelligence, which has a wide range of applications. In particular, it becomes an indispensable part of computer systems dealing with complex problems, difficult or infeasible to solve by means of conventional algorithms.

In computational intelligence, machine learning algorithms are used to build models of systems or processes, which are based on experimental data and offer good generalization properties. This means that such data-driven models can be applied to make reliable predictions or decisions for new data which were not previously available during the learning process. At present, machine learning is an important element of intelligent computer systems with numerous applications in engineering, medicine, economics, education, etc.

The aim of this Topical Collection is to provide a comprehensive appraisal of innovative applications of machine learning algorithms in computer engineering employing novel approaches and methods, including deep learning, hybrid models, multimodal data fusion etc.

This Topical Collection will focus on the applications of machine learning in different fields of computer engineering. Topics of interest include but are not limited to the following:

• Machine learning and decision making in engineering and economics;
• Intelligent sensors and systems in machine vision and control;
• Machine learning methods to process monitoring and prediction;
• Pattern recognition in medical diagnosis;
• Big data analysis;
• Natural language processing;
• AI-based efficient energy management;
• Deep learning architectures;
• Data-driven models;

Machine learning in different applications.

Prof. Dr. Lidia Jackowska-Strumillo
Collection Editor

Manuscript Submission Information

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