Research Communication | Open Access
Volume 2021 | Communication ID 216
Volume 2021 | Communication ID 216
| Object Detection, Parallel Processing : A state-of-art and Challenges |
Safae Msellek
Received |
Accepted |
Published |
January 31, 2021 |
February 15, 2021 |
March 15, 2021 |
Abstract: In the past few years, object detection has attracted a lot of interest in scientific research for its relevance in areas requiring complicated processing or artificial intelligence. The goal is to find and identify possible instances of specific objects, such as vehicles, people or body parts by using sequential or parallel processing and procedures to achieve real-time performance. The objective of this communication is to present a state of art of several obstacle detection algorithms (traditional approaches, machine learning and deep learning methods) and with the use of a comparative ...