Application, Optimization and Architecture of Deep Learning Neural Network, 2nd Edition
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 20 July 2026 | Viewed by 17
Special Issue Editor
Interests: cloud computing; big data; deep learning; IoT; wireless networks
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
With the surge in images and videos that need to be processed, deep learning neural networks are becoming a popular and essential tool for solving various problems, such as classification, detection, and regression. The new deep architectures have led to advances in computational resources and to more reliable results.
Therefore, in this Special Issue, we aim to present novel deep learning algorithms and their applications in various research fields. Submitted articles can cover various topics, including, but not limited to, deep learning, artificial intelligence, the processing of large datasets from medical instruments, ground-based datasets, scientific experiments, and many other sources.
Dr. Haigang Gong
Guest Editor
Manuscript Submission Information
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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. 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.
Keywords
- deep learning
- artificial intelligence
- reinforcement learning
- image detection and segmentation
- forecasting using deep networks
- predications using deep networks
- applications of deep learning neural networks
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