Design and Implementation of Touch Display Accuracy Optimization Software Based on Deep Learning
This paper mainly introduces the touch display accuracy optimization software based on convolutional neural network to enhance the touch accuracy of the smart board system. Convolutional neural networks are used to train touch data, which enables the software to automatically correct the position of touch points and reduce touch bias. The system architecture includes a data acquisition module, a deep learning model training module, and a touch accuracy optimization module, which is expected to be applied to more fields with the continuous application and development of technology. On the whole, the launch of the software provides a new technical way to realize the smart board book system.
Authors
- Ziqiu Wang
Institutions
- Southwest Petroleum University (CN)
Publication Details
- Journal
- International Journal of Computer Science and Information Technology
- Published
- 2024-09-13
- DOI
- https://doi.org/10.62051/ijcsit.v4n1.29
- Primary Topic
- E-commerce and Technology Innovations
- Type
- article
- Field-Weighted Citation Impact
- 0.00