RT Journal Article
T1 Visual Object Detection with DETR to Support Video-Diagnosis Using Conference Tools
A1 Biró, Attila
A1 Tünde Janosi-Rancz, Katalin
A1 Szilágyi, László
A1 Cuesta-Vargas, Antonio
A1 Martín-Martín, Jaime
A1 Miklós Szilágyi, Sándor
K1 Diagnóstico por imagen
AB This text discusses the need for real-time multilingual sentence detection during online video presentations, particularly in the healthcare sector for remote diagnosis. The use of visual (textual) object detection and preprocessing is essential for subsequent analysis. The researchers propose using the DEtection TRansformer (DETR) model to achieve accurate and real-time detection of textual objects. The development of real-time videoconference translation supported by artificial intelligence has become especially important during the COVID-19 pandemic. The challenge lies in the variety of languages spoken by specialists, which requires human translators or AI-based technological channels. The accuracy of visual localization of textual elements depends on the complexity, quality, and variety of the training datasets. The researchers compare the performance of the DETR model with other real-time object detectors like YOLO4 and Detectron2, and introduce AI-based innovations through collaborative solutions combined with OCR. The researchers conducted evaluations using training datasets and achieved higher-than-expected accuracy in terms of visual text detection range, with an average accuracy of 0.4 to 0.65.
PB MDPI
YR 2022
FD 2022-06-12
LK https://hdl.handle.net/10630/32668
UL https://hdl.handle.net/10630/32668
LA eng
NO Biró, A.; Jánosi-Rancz, K.T.; Szilágyi, L.; Cuesta-Vargas, A.I.; Martín-Martín, J.; Szilágyi, S.M. Visual Object Detection with DETR to Support Video-Diagnosis Using Conference Tools. Appl. Sci. 2022, 12, 5977. https://doi.org/10.3390/app12125977
NO This research was supported by ITware, Hungary. The work of K.T. Jánosi-Rancz and L. Szilágyi was supported by Sapientia Foundation—Institute for Scientific Research.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 19 ene 2026