Implementation of ResNet-50 on End-to-End Object Detection (DETR) on Objects

Authors

  • Endang Suherman Universitas Pradita, Serpong, Banten, Indonesia
  • Ben Rahman Fakultas Teknologi Komunikasi dan Informatika, Universitas Nasional, Indonesia
  • Djarot Hindarto Fakultas Teknologi Komunikasi dan Informatika, Universitas Nasional, Indonesia
  • Handri Santoso Universitas Pradita, Serpong, Banten, Indonesia

DOI:

10.33395/sinkron.v8i2.12378

Keywords:

CNN, Computer Vision COCO Dataset, End-to-End Object Detection, Object Detection, ResNet-50

Abstract

Object recognition in images is one of the problems that continues to be faced in the world of computer vision. Various approaches have been developed to address this problem, and end-to-end object detection is one relatively new approach. End-to-end object detection involves using the CNN and Transformer architectures to learn object information directly from the image and can produce very good results in object detection. In this research, we implemented ResNet-50 in an End-to-End Object Detection system to improve object detection performance in images. ResNet-50 is a CNN architecture that is well-known for its effectiveness in image recognition tasks, while DETR utilizes Transformers to study object representations directly from images. We tested our system performance on the COCO dataset and demonstrated that ResNet-50 + DETR achieves a better level of accuracy than DETR models that do not use ResNet-50. In addition, we also show that ResNet-50 + DETR can detect objects more quickly than similar traditional CNN models. The results of our research show that the use of ResNet-50 in the DETR system can improve object detection performance in images by about 90%. We also show that using ResNet-50 in DETR systems can improve object detection speed, which is a huge advantage in real-time applications. We hope that the results of this research can contribute to the development of object detection technology in images in the world of computer vision.

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How to Cite

Suherman, E. ., Rahman, B. ., Hindarto, D. ., & Santoso, H. . (2023). Implementation of ResNet-50 on End-to-End Object Detection (DETR) on Objects. Sinkron : Jurnal Dan Penelitian Teknik Informatika, 7(2), 1085-1096. https://doi.org/10.33395/sinkron.v8i2.12378

Issue

Vol. 7 No. 2 (2023): Research Article, Volume 7 Issue 2 April, 2023

Section

Articles

License

Copyright (c) 2023 Endang Suherman, Ben Rahman, Djarot Hindarto, Handri Santoso

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

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