Special Issue "Recent Progress in Deep Symmetry Networks: Applications and Future Trends"

Dear Colleagues,

Due to recent improvements in Deep Learning (DL), relevant applications are rapidly developing, with a large amount of research being undertaken. Symmetry has been employed for decades in the natural sciences as a key and wide notion in comprehending natural principles. Recently, several academics have applied the notion of symmetry to DL models and architecture. Their strategy has the potential to minimize training complexity, training duration, and over-fitting. Complex deep neural networks are transforming a wide range of fields, from image-based medical diagnostics and self-driving cars to smart models used in robots, e-commerce, financial applications, voice and text recognition, and visual art. In information processing, symmetry has the effect of reducing complexity by translating it into simpler forms. The goal of this Special Issue, " Recent Progress in Deep Symmetry Networks: Applications and Future Trends," is to concentrate on all elements of DL in the fields of symmetry-based DL algorithms, multimedia-enabled IoT-distributed systems, and intelligent human–computer interaction for both theoretical and practical applications. Authors are requested to submit exceptional and unique unpublished research publications focusing on the most recent discoveries in this subject. It will be beneficial for specialists in this industry to share the most recent technological breakthroughs. The topics of interest include, but are not limited to:

• Deep symmetry applications in learning-based algorithms for imaging;
• Deep symmetry applications in automated approaches to localizing and tracking moving targets in unmanned aerial vehicles and the internet of drones;
• Deep symmetry applications in deep neural networks in discovery-based applications;
• Deep symmetry applications in deep neural networks in smart city applications;
• Deep symmetry applications in detection and segmentation of images in medical healthcare;
• DL for symmetry in IoT network;
• New DL algorithms and architectures for deep symmetry;
• Deep symmetry for multimedia-enabled IoT and distributed systems;
• Deep symmetry for image/video recognition and deepfake detection;
• Deep symmetry for style transfer and generative adversarial network;
• Deep symmetry for intelligent human–computer interaction.

Dr. Nima Jafari Navimipour
Dr. Abdulsalam Yassine
Dr. Lila Rajabion
Dr. Arash Heidari
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 100 words) can be sent to the Editorial Office for announcement on this website.

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. Symmetry 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 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.