Qt Based Video Streaming Software for Recording Video during Experiments using Deep Learning
This research paper introduces a Qt-based video streaming software designed to facilitate the recording of video data during experiments employing Deep Learning capabilities. The software provides a user-friendly interface for seamless video capture, enabling researchers to efficiently document experimental processes. Leveraging the capabilities of the Qt framework, the software provides robustness, flexibility, and cross-platform compatibility. Integrating Deep Learning enhances the software's functionality by enabling automated analysis and annotation of recorded videos. This tool serves as a valuable resource for researchers across various domains requiring precise video documentation and analysis during experimental procedures.
Authors
- Arpit Singh (ORCID: https://orcid.org/0000-0001-6205-6200)
- Jhanvi Lamba
- Yash Raj Singh (ORCID: https://orcid.org/0000-0002-4664-1968)
Institutions
- SRM Institute of Science and Technology (IN)
Publication Details
- Published
- 2024-09-20
- DOI
- https://doi.org/10.1109/i3ceet61722.2024.10993967
- Primary Topic
- Industrial Vision Systems and Defect Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00