Applications of Deep Learning and Convolutional Neural Network
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E1: Mathematics and Computer Science".
Deadline for manuscript submissions: 20 December 2025 | Viewed by 1910
Special Issue Editor
Special Issue Information
Dear Colleagues,
The Special Issue, titled "Applications of Deep Learning and Convolutional Neural Networks", explores the transformative impacts of these technologies across diverse fields, showcasing cutting-edge research and innovative applications. Deep learning and CNNs have revolutionized the way we approach complex data problems, offering powerful tools for pattern recognition, image and speech processing, natural language understanding, etc.
In this Special Issue, we feature articles that highlight the versatility and adaptability of deep learning models. We delve into the use of CNNs for medical image analysis, where they significantly enhance diagnostic accuracy and enable early detection of diseases. In the realm of autonomous vehicles, deep learning algorithms facilitate real-time object detection and decision-making, paving the way for safer transportation systems.
Moreover, this Special Issue explores the role of deep learning in financial technology, where predictive models are employed for risk assessment and fraud detection, optimizing financial operations. Another key focus is the application of CNNs in environmental monitoring, where satellite imagery is analyzed to track climate change and natural resource management.
Overall, this Special Issue will provide a comprehensive overview of how deep learning and CNNs are leveraged to address pressing global challenges, highlighting both achievements and ongoing challenges in this rapidly evolving field.
Dr. NIwat Angkawisittpan
Guest Editor
Manuscript Submission Information
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Keywords
- deep learning
- convolutional neural networks (CNNs)
- pattern recognition
- medical image analysis
- diagnostic accuracy
- autonomous vehicles
- real-time object detection
- decision-making financial technology (FinTech)
- risk assessment
- fraud detection
- environmental monitoring
- satellite imagery
- climate change tracking
- natural resource management
- artificial intelligence (AI)
- image and speech processing
- natural language understanding
- predictive models
- global challenges in AI
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