Special Issue:”Survey in Deep Learning for IoT Applications”
Deadline for manuscript submissions: 31 December 2022
Website: https://www.mdpi.com/journal/computers/special_issues/DL_iot
Guest Editor: Dr. Rytis Maskeliunas, Prof. Dr. Robertas Damaševičius,
University of Technology, Kaunas, Lithuania.

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Dear Colleagues,

In recent years, methods and dedicated communication channels of the
Internet of Things (IoT) have been developed to detect and collect all
kinds of information to deliver a variety of advanced services and
applications, generating huge amounts of data, constantly received from
millions of IoT sensors deployed around the world. The techniques behind
deep learning now play an important role in desktop and mobile
applications and are now entering the resource-constrained IoT sector,
enabling the development of more advanced IoT applications, with proven
results in a variety of areas already, including image recognition,
medical data analysis, information retrieval, language recognition,
natural language processing, indoor location, autonomous vehicles, smart
cities, sustainability, pollution, bioeconomy, etc. This Special Issue
focuses on the research and application of the Internet of Things,
focusing on multimodal signal processing, sensor extraction, data
visualization and understanding, and other related topics, answering the
question of which deep neural network structures can efficiently process
and integrate multimodal sensor input data for various IoT applications,
how to adapt current and develop new designs to help to reduce the
resource cost of running deep learning models for the efficient
deployment on IoT devices, how to correctly calculate reliability
measurements in deep learning predictions for IoT applications within
limited and constrained calculation requirements, how to reduce the use
of labeled IoT for needs linked to learning signal data considering
operational limitations and other key areas.

Keywords
Internet of Things
Deep learning
Data fusion
Multimodal signal processing
Data processing and visualization

Prof. Dr. Robertas Damaševičius
Dr. Rytis Maskeliunas
Guest Editors
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