Deep Neural Network: Algorithms and Applications
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: closed (20 June 2023) | Viewed by 16974
Special Issue Editors
Interests: artificial intelligence; machine learning; deep learning; oceanography; mathematical modelling; climate change; environmental modelling
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Deep neural networks have become an important and popular tool for solving various tyes of classification, clustering, and regression problems. The new deep learning architectures offer many advancement in computational ability for highly accurate and reliable results. Deep learning also features as a highly active field for image and signal processing.
Therefore, this Special Issue is intended for the presentation of novel algorithms and their applications in various areas of research, including the natural sciences, engineering and the built environment, information technology, social sciences, and business/economics. Areas relevant to deep learning networks and their applications include, but are not limited to, artificial intelligence, machine learning, deep learning, and the processing of large datasets from satellites, ground based datasets, scientific experiments, sensor networks, medical instruments, and many other sources.
This Special Issue will publish high-quality, original research papers, in the overlapping fields of:
- Artificial intelligence;
- Machine learning;
- Deep learning;
- Computational and data science;
- Big data applications, algorithms, and systems;
- Hardware and software optimized for artificial intelligence and machine learning;
- New applications of artificial intelligence and machine learning;
- Forecasting and predictions using deep learning neural network.
Dr. Nawin Raj
Dr. Jason Brown
Guest Editors
Manuscript Submission Information
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Keywords
- deep neural network
- deep learning architecture and algorithms
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