Advances in Deep Learning, Computer Vision, and Engineering Applications
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E: Applied Mathematics".
Deadline for manuscript submissions: 20 June 2025 | Viewed by 784
Special Issue Editors
Interests: machine learning; physics-informed machine learning; computer vision; structural health monitoring; deep learning
Special Issues, Collections and Topics in MDPI journals
Interests: mathematics in deep learning; computer vision; 3D reconstruction; diffusion models
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
We are pleased to invite you to contribute to this Special Issue on "Advances in Deep Learning, Computer Vision, and Engineering Applications" with an original research article that focuses on the development of deep learning, computer vision, and their applications within the context of computational engineering and applied mathematics.
As engineering systems and mathematical models grow increasingly complex, the demand for precise algorithms and efficient computational methods has never been higher. This Special Issue aims to showcase innovative mathematical and computational approaches in areas such as expressive power of deep neural networks, optimal training of deep learning networks, efficient parallel computation with GPUs, compression, quantization and interpretation of deep learning models, 3D reconstruction from 2D images, structural health monitoring, data-driven scientific simulation, and physics-informed neural networks. These areas, where deep learning and computer vision intersect with advanced mathematical modeling, are essential for advancing theoretical research and practical implementations in machine learning design and engineering.
We particularly encourage contributions that introduce novel mathematical theories or advanced machine learning techniques and demonstrate their efficacy in addressing real-world engineering challenges, thereby bridging the gap between mathematical concepts and their practical engineering applications.
Dr. Qilin Li
Dr. Senjian An
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. Mathematics 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 2600 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
- deep learning
- machine learning
- diffusion models
- expressive power of deep neural networks
- computer vision
- engineering mathematics
- computational engineering
- 3D reconstruction
- data-driven simulation
- physics-informed neural networks
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