Research Article
The Object Detection, Perspective and Obstacles In Robotic: A Review
@ARTICLE{10.4108/airo.v1i1.2709, author={Ge Xu and Amir Sohail Khan and Ata Jahangir Moshayedi and Xiaohong Zhang and Yang Shuxin}, title={The Object Detection, Perspective and Obstacles In Robotic: A Review}, journal={EAI Endorsed Transactions on AI and Robotics}, volume={1}, number={1}, publisher={EAI}, journal_a={AIRO}, year={2022}, month={10}, keywords={Deep Learning, Object Detection, Image Processing, Salient Object Detection (SOD), 3D object detection}, doi={10.4108/airo.v1i1.2709} }
- Ge Xu
Amir Sohail Khan
Ata Jahangir Moshayedi
Xiaohong Zhang
Yang Shuxin
Year: 2022
The Object Detection, Perspective and Obstacles In Robotic: A Review
AIRO
EAI
DOI: 10.4108/airo.v1i1.2709
Abstract
A few years back, when the image processing hardware and software were created, it was limited, and most of the time, object detection would fail., But as with time, the advancement in technology has significantly changed the scenario. A lot of researchers worked in this field to carry out a solution through which they can detect objects in any field, especially in the robotic domain [1]. In today's world, with so much research in the field of deep learning, it is very easy to identify and detect any object using computer vision. This paper focuses on the various deep learning technologies and algorithms through which object detection can be done. A new and advanced deep learning technology known as salient object detection has been discussed. Also, the 3D object detection and the end-to-end approach for object detection are discussed. The existing methods of deep learning through which object detection can be done. The applications in which object detection is being used and the importance of object detection. It also reports; what the predecessors have done, what problems have been solved by them, how they solved these problems, the characteristics of the predecessors' methods and their future work.
Copyright © 2022 Ge Xu et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.