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Implementation and Performance Analysis of Mobile Real-Time Frame Interpolation Network Using Deep Learning
- Author(s)
- 안현모
- Advisor
- 황원준
- Department
- 일반대학원 인공지능학과
- Publisher
- The Graduate School, Ajou University
- Publication Year
- 2023-08
- Language
- eng
- Alternative Abstract
- This research emphasizes the importance of constructing an efficient deep learning model that can perform real-time video frame interpolation in resource-constrained mobile environments, amidst the rapid advancements in the field of deep learning technology. <br>The study proposes a lightweight network model and system for real-time video frame interpolation in mobile environments. <br>By integrating intelligent data adjustment, lightweight CNN architecture, and distributed computing techniques, the model is designed to operate efficiently even with limited resources. <br>The proposed lightweight network model contributes to the field of video frame interpolation by providing a lightweight solution tailored to mobile environments. <br>It also opens up possibilities for various industries where efficient storage utilization and high frame rates are crucial. <br>Furthermore, the research provides insights into lightweight techniques and distributed computing strategies that can be applied to other deep learning models in resource-constrained environments.
- Fulltext
- Appears in Collections:
- Graduate School of Ajou University > Department of Artificial Intelligence > 3. Theses(Master)
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