Deep Learning Based Approaches in Signal Processing and IoT: A Pathway to Intelligent Systems (DLIOT)

Signal and Image processing have become indispensible technologies in current time, this is the era of artificial intelligence and such systems cannot function without signal processing. These techniques find its marks in areas like computer vision, image analysis, pattern recognition, medicine, etc. These signals are produced from various devices and sensors, which form a network in itself. IoT is the best choice to make this network intelligent. IoT is trying to make such devices and sensors (most of these are the objects that we use in our day to day life) smarter. There is a continuous inflow of data from these sensors and devices, it is not possible to manage and analyze this data manually. The outcome depends on the processing of high-dimensional data and most of it is irregular and unordered, present in variety of forms like text, images, videos, audio, graphics, etc.

This hybrid data creates new challenges for development of effective solutions and algorithms, therefore a technology is required which can work smoothly in such heterogeneous computing environment, deep learning wins hands down here. Deep learning is a revolutionary technology in this diverse area, where result is data driven, so it is high time to explore advancements in deep learning algorithms.

The intermingling disciplines of signal/image processing and IoT are pathway towards intelligent systems and deep learning forms a bridge between technologies, this field have attracted researchers in past and will continue to do so. The research covers numerous multidisciplinary topics catering towards academia and industries.

This Virtual Special Issue (VSI) intends to bring together researchers and developers from academic fields and industries worldwide working in the broad areas of Image processing and promote community-wide discussion of ideas that will influence and foster continued research in this field for the betterment of human mankind.

Recommended topics include (but are not limited to) the following:

• Bio-Medical data analysis
• Internet of Things based Security
• Internet of Things and AI based Smart homes
• Securities issues in signal processing and IoT
• Pattern recognition
• Data reduction and feature extraction
• Deep Learning and IoT for Smart City Solutions
• Deep learning in Text Processing

Tentative schedule

• Start of submission period: April 1st, 2020
• Deadline for submission: 30th April, 2020
• First review notification: June 25, 2020
• Revision submission: September 30, 2020
• Second review notification: November 30th, 2020
• Final Acceptance notification to authors: December 20th, 2020
• Online Publication: December 2020

Paper submission:

Papers will be evaluated based on their originality, presentation, relevance and novelty, as well as their suitability to the special issue, and for their overall quality, giving preference to those with accompanying data, demo, and software. Author guidelines for preparation of manuscript can be found at: http://www.elsevier.com/journals/pattern-recognition-letters/0167-8655/guide-for-authors.The submission website for this journal is located at: http://ees.elsevier.com/prletters/default.asp. To ensure that all manuscripts are correctly identified for inclusion into the special issue, it is important that authors select “SI: DLIOT” when they reach the “Article Type Name” step in the submission process. Note that a maximum of 10 pages in the Journal layout is admitted for special issue papers.

Review process

Guest editors will make an initial determination of the suitability and scope of all submissions. The review process will be done by following the standard review process of Pattern Recognition Letters. Each paper will be reviewed by at least two experts in the field. In general, only two reviewing rounds will be possible, out of which major revision is possible only for the first round. Papers that after the 2nd reviewing round still need major revision will be rejected.