Machine Learning Techniques for Image Processing
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".
Deadline for manuscript submissions: 16 November 2024 | Viewed by 1296
Special Issue Editors
Interests: machine learning; image processing; signal processing; computer sciences; artificial intelligence; pattern recognition
Special Issues, Collections and Topics in MDPI journals
Interests: computer engineering; cyber–physical systems; software defined networks
Special Issues, Collections and Topics in MDPI journals
Interests: robotics; mobile robotics; control systems; intelligent algorithms
Special Issue Information
Dear Colleagues,
Today, machine learning and image processing are applied in every field of science and technology.
In the real world, in addition to traditional image processing methods, there are machine learning algorithms for complex and diverse image data, data-driven approaches, and applications where models can learn from large amounts of labeled or unlabeled image data to automatically discover patterns, properties, and relationships.
Various machine learning techniques, such as convolutional neural networks, which are widely used in image processing and perform outstandingly in tasks such as image classification, object detection, and semantic segmentation, find wide-ranging applications in industry, health, agriculture, finance, and social sciences. Studies related to industrial, biomedical data applications, autonomous vehicle and drone technologies, agriculture and cartography, computational sciences, finance, marketing and advertising are within the scope of this Special Issue, which hopes to be a platform to explore all machine learning-based applications.
In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:
- Medical science;
- Biomedical science;
- Statistics and mathematics;
- Engineering/industrial systems;
- Computer and computational sciences;
- Electric, electronic, and mechatronic systems;
- Autonomous vehicles;
- Aviation and drone technologies;
- Energy systems;
- Material science;
- Finance;
- Marketing, advertising, and management;
- Psychology;
- Social media.
We look forward to receiving your contributions.
Dr. Tahir Cetin Akinci
Dr. Mustafa Ilhan Akbas
Dr. Gokhan Erdemir
Dr. Oguzhan Topsakal
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. 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.
Keywords
- machine learning
- deep learning
- artificial neural networks
- artificial intelligence
