Year: 2023
Type: preprint
Abstract: Real-time object detection is a crucial problem to solve when in comes to computer vision systems that needs to make appropriate decision based on detection in a timely manner. I have chosen the YOLO v1 architecture to implement it using PyTorch framework, with goal to familiarize with entire object detection pipeline I attempted different techniques to modify the original architecture to improve the results. Finally, I compare the metrics of my implementation to the original.
Source: arXiv (Cornell University)
Author: Shenoda, Michael
Institution: Drexel University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4378768534