Deep and Classic Machine Learning in Signal, Image, and Video Analysis

Dear Colleagues,

The recent domination of machine learning, especially deep learning techniques, in sensor analysis research has, among others, raised questions about the new positioning of classic, analytic solutions in signal, image and video processing. Aside from the unprecedented success of machine learning, there are some weak points of its use, especially for low- and mid-level sensor analysis. This is due to its strong dependence on large data sets, typically requiring annotation by human experts, and heavy solutions with a huge number of trainable parameters, typically leading to extensive training and processing resources.

In this Special Issue, we are particularly interested in how a knowledge-aware preprocessing of training data (i.e., data refinement, ordering, normalization, feature extraction, etc.) can drive lightweight deep neural networks to achieve similar performance as existing complex and powerful “heavy” networks.

The application tasks solved in this may include various signal analysis and classification, speech and speaker recognition, semantic image segmentation and visual object recognition, object tracking, human action and interaction classification in video and RGB-D sequences, and other problems in sensor analysis.

Through the proposed topic, our Special Issue is expected to contribute to a successful synergy between long-time-existing highly specialized, vast amounts of computational methods in signal and image analysis, and deep learning techniques steadily being developed by the machine learning community.

Prof. Dr. Włodzimierz Kasprzak
Guest Editor

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-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly 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 2400 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.