New Advances and Challenges in Neural Networks and Applications
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E: Applied Mathematics".
Deadline for manuscript submissions: 30 September 2025 | Viewed by 1689
Special Issue Editors
Interests: deep neural network; multimodal integration; representation learning; model calibration; neural network vulnerability; uncertainty estimation; computer vision; medical imaging; remote sensing
Special Issue Information
Dear Colleagues,
Neural networks have become one of the most popular tools, with promising results in a variety of domains ranging from general computer vision to domain-specific tasks, from remote sensing to astrophysics and astronomy, and from natural language processing to multimodal integration systems. Without a doubt, neural networks are one of the most exciting research fields. However, as neural networks become more popular, new challenges emerge.
We are delighted to invite you to contribute an original research article focused on new advances and challenges in modern neural networks and their applications to this Special Issue entitled “New Advances and Challenges in Neural Networks and Applications”.
The broad topics include, but are not limited to, the following:
- Existing and potential challenges of neural networks, such as vulnerability, robustness, calibration, interpretability, etc.
- Emerging issues of neural networks, such as potential threats to cyber security and their defense (e.g., deep fakes and large-scale information generation).
- Novel neural network algorithms, applications, usage cases, and datasets in various domains, such as medical imaging, autonomous driving, remote sensing, smart assistants, language–vision integration, agriculture, and pest control.
Dr. Gongbo Liang
Prof. Dr. LiangLiang Liu
Guest Editors
Manuscript Submission Information
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Keywords
- deep learning
- computer vision
- natural language processing
- medical imaging, remote sensing, agriculture, and domain-specific applications
- model calibration, vulnerability, robustness, interpretability, etc.
- classification, segmentation, and detection
- language-vision integration
- cyber security
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