Computing Systems for Embedded Deep Learning

Dear Colleagues,

Smart embedded systems have recently been the focus of intensive research and development due to their significant potential to improve the quality of human life in areas such as healthcare, security and safety, home living, city living and many others. Machine learning algorithms can be used to design intelligent embedded devices. Recently, deep neural networks (DNN), such as CNN, RNN, LSTM, GAN and SNN, have achieved superior performances in accuracy when compared to other machine learning algorithms, but they require more computing and memory resources, as well as energy. However, computing platforms of embedded systems have limited computing power, memory and energy. So, the implementation of DNNs in embedded systems is currently a major topic in the scientific community and requires further innovation in its development and application. This Special Issue aims to collect recent research with a focus on deploying DNNs in embedded computing systems. Potential topics include, but are not limited to:

• DNN models for embedded systems;
• Optimization of DNN models for embedded computing;
• Quantization and sparsification of DNN models;
• Implementation of DNN in embedded GPUs;
• Implementation of DNN in low-cost computing platforms;
• Reconfigurable architectures for DNN in embedded systems;
• Very low-power embedded platforms for DNNs;
• Coarse-grained reconfigurable architectures for embedded deep learning;
• Design methodologies for DNN on embedded systems;
• Design of DNN for IoT devices;
• Software tools to help design smart embedded systems;
• Applications of DNN on health, smart homes, smart cities, security, surveillance, etc.;
• Smart embedded systems for industrial IoT;
• Designing DNN for robotics.

Dr. Mário Véstias
Dr. Pedro Miguel Florindo Miguens Matutino
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Future Internet is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.