Dumitrascu Razvan-George
Dumitrascu Razvan-George has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Besnea Petcu Florina Luminita
Mechatronics and Robotics Department, University of Craiova, 200440 Craiova, Romania
1 shared publication - Dorin Șendrescu
Department of Automatic Control and Electronics, University of Craiova, 200585 Craiova, Romania
1 shared publication - Gagiu Daniel-Gheorghe
Department of Automatic Control and Electronics, University of Craiova, 200585 Craiova, Romania
1 shared publication - Ștefan Irinel Cismaru
Department of Mechatronics and Robotics, University of Craiova, RO-200440 Craiova, Romania
1 shared publication
Latest Publications
- Open Access
- 20 May 2025
- Published by University of Craiova in Annals of the University of Craiova Mathematics and Computer Science Series
- Vol. 52 (1) , 272-287
TV production application based on Artificial Intelligence specific algorithms
The paper proposes an application that integrates an artificial intelligence model and is intended for the television production environment. This uses a pre-trained model, capable of quickly and accurately identifying relevant video files in a vast archive. This process involves the automatic analysis of metadata and audio-visual content to detect the information sought in each file, resulting in a list of files that match the selection criteria made with the help of implemented YOLO-type algorithms. The application is powered by an artificial intelligence model that can be customized and continuously created through additional training, using input data provided by users. Thus, an efficient and adaptable solution is created, which optimizes archive management and improves the production flow. The proposed application aims to eliminate the time spent identifying audio-video material necessary for editing.
- 20 May 2025
- Published by University of Craiova in Annals of the University of Craiova Mathematics and Computer Science Series
- Vol. 52 (1) , 272-287
Open AccessTV production application based on Artificial Intelligence specific algorithms
The paper proposes an application that integrates an artificial intelligence model and is intended for the television production environment. This uses a pre-trained model, capable of quickly and accurately identifying relevant video files in a vast archive. This process involves the automatic analysis of metadata and audio-visual content to detect the information sought in each file, resulting in a list of files that match the selection criteria made with the help of implemented YOLO-type algorithms. The application is powered by an artificial intelligence model that can be customized and continuously created through additional training, using input data provided by users. Thus, an efficient and adaptable solution is created, which optimizes archive management and improves the production flow. The proposed application aims to eliminate the time spent identifying audio-video material necessary for editing.