Title: "Research using DETR model for Object Detection in Non-Imagery"
Author: Ngô Hương Giang – 22520357 – KTPM2022.1 – Primary Author
Supervisors:
TS. Nguyễn Tấn Trần Minh Khang
ThS. Nguyễn Thị Thanh Trúc
Abstract:
The early detection of objects in non-image scenarios has become an increasingly intriguing topic with the advancement of technology. Several end-to-end Transformer-based models have been proposed to address this problem. Our research focuses on the DETR approach, a foundational model that combines the Transformer architecture of many contemporary end-to-end models on the VisDrone dataset. We observed its automatic adjustment capabilities for specific situations based on training data. The study on DETR has provided valuable insights into how the Transformer architecture can be applied to object detection in non-images. This marks a significant advancement in this field, paving the way for future research to enhance the performance of DETR and similar models.
We express our sincere gratitude to the Faculty of Software Engineering, Multimedia Communications Lab, and the UIT-Together research group for creating the conditions that enabled us to conduct and complete this research.
In contributing to the advancement of fundamental and applied information technology research in Vietnam, the Vietnam Union of Science and Technology Associations, the Vietnam Academy of Science and Technology, in coordination with the University of Technical Education - University of Danang, and various scientific institutions, are organizing the 16th National Scientific Conference on "Fundamental and Applied Information Technology" (FAIR'2023).
The main theme of the conference is "Data Science in the Digital Transformation."
The conference will take place at the University of Technical Education - University of Danang on Thursday and Friday, September 28-29, 2023.
Detailed Information:
Hai Bang - Communication Collaborator, University of Information Technology
English version: Phan Huy Hoang
