Submission Deadline: 31 March 2020
IEEE Access invites manuscript submissions in the area of Advances in Machine Learning and Cognitive Computing for Industry Applications.
Over the past few years, great progress has been made due to advances in machine learning and cognitive computing. For example, with the adoption of Convolutional Neural Networks (CNNs), computer vision has surpassed human vision in the task of image recognition. Moreover, the improvement in Natural Language Processing (NLP) makes machine translation, speech recognition, and other sequence applications more powerful than ever. It is the significant progress of machine learning algorithms, computing capability, and big data that makes machine learning and cognitive computing increasingly powerful in many applications. Compared to machine learning, cognitive computing places more emphasis on how the human brain works. Cognitive computing simulates human thought processes with self-learning algorithms that utilize data mining, pattern recognition, and natural language processing. In industrial scenarios, the data amount, as well as data generation speed, is very different compared to standard machine learning data sets. It is a challenge to utilize these heterogeneous data and find meaningful insights for practical applications.
As the basis, the Internet of Things (IoT) middleware platforms, communication, and network ecosystems should be involved. Considering the heterogeneity of industrial data, we are expected to inspect, clean, transform, and model data with the goal of specific industrial applications. Moreover, specialized algorithms, computing architectures, and feature engineering are needed to review, analyze, and present information. With the support of machine learning and cognitive computing, the significant insights and knowledge hidden behind industrial data can be capitalized for process optimization, anomaly detection, energy management, and so on. This Special Section focuses on consolidating research efforts that aim at machine learning and cognitive computing for industrial applications.
The topics of interest include, but are not limited to:
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Associate Editor: Min Xia, Lancaster University, United Kingdom
Relevant IEEE Access Special Sections:
IEEE Access Editor-in-Chief: Prof. Derek Abbott, University of Adelaide
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