Computer Vision and Machine Learning: Theory, Methods and Applications

Dear Colleagues,

Computer vision (CV) and machine learning (ML) now represent two of the most addressed topics in artificial intelligence and computer science. The field of computer vision has witnessed an incredible shift in the last decade with the advent of deep learning, by means of which new applications have emerged and new milestones have been made reachable. Deep learning represents the most noticeable point of connection between CV and ML, but there is still much to be discovered in all these fields.

This Topical Collection will gather papers proposing advances in theory and models in CV and ML, paving the way to new applications.

Hence, we invite the academic community and relevant industrial partners to submit papers to this collection, on relevant fields and topics including (but not limited to) the following:

• New algorithms and methods of classical computer vision.
• Architecture and applications of convolutional neural networks.
• Transformers applied to computer vision.
• Geometric deep learning and graph convolution networks.
• Generative adversarial networks (GAN).
• Generative models beyond GANs.
• Fairness, privacy, and explainability in deep learning.
• Continual, online, developmental, and federated learning.
• Zero- and few-shot learning.
• Brand new applications of computer vision and machine learning.

Prof. Dr. Andrea Prati
Prof. Dr. Yuan-Kai Wang
Collection 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. 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 collection 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. Applied Sciences 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.