Special Issue "Convolutional Neural Networks and Vision Applications"
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Artificial Intelligence Circuits and Systems (AICAS)".
Deadline for manuscript submissions: closed (15 July 2021) | Viewed by 14847
Interests: artificial intelligence; high-performance visual computing; robotic vision; real-time visual inspection automation
Special Issues, Collections and Topics in MDPI journals
Special Issue in Electronics: 10th Anniversary of Electronics—Hot Topic in Artificial Intelligence Circuits and Systems
Special Issue in Electronics: Convolutional Neural Networks and Vision Applications, Volume II
Processing speed is critical for visual inspection automation and mobile visual computing applications. Many powerful and sophisticated computer vision algorithms generate accurate results but require high computational power or resources and are not entirely suitable for real-time vision applications. On the other hand, there are vision algorithms and convolutional neural networks that perform at camera frame rates but with moderately reduced accuracy, which is arguably more applicable for real-time vision applications. This special issue is for research related to the design, optimization, and implementation of machine learning-based vision algorithms or convolutional neural networks that are suitable for real-time vision applications.
General topics covered in this special issue include, but are not limited to:
- Optimization of software-based vision algorithms
- CNN architecture optimizations for real-time performance
- CNN acceleration through approximate computing
- CNN applications that require real-time performance
- Tradeoff analysis between speed and accuracy in CNN
- GPU-based implementations for real-time CNN performance
- FPGA-based implementations for real-time CNN performance
- Embedded vision systems for applications that require real-time performance
- Machine vision applications that require real-time performance
Prof. Dr. D. J. Lee
Manuscript Submission Information
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