Continual Learning Strategy in One-Stage Object Detection Framework Based on Experience Replay for Autonomous Driving Vehicle
Object detection is an important aspect for autonomous driving vehicles (ADV), which may comprise of a machine learning model that detects a range of classes. As the deployment of ADV widens globally, the variety of objects to be detected may increase beyond the designated range of classes. Continua...
Main Authors: | Jeng-Lun Shieh, Qazi Mazhar ul Haq, Muhamad Amirul Haq, Said Karam, Peter Chondro, De-Qin Gao, Shanq-Jang Ruan |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-11-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/20/23/6777 |
Similar Items
-
Transferable Architecture for Segmenting Maxillary Sinuses on Texture-Enhanced Occipitomental View Radiographs
by: Peter Chondro, et al.
Published: (2020-05-01) -
FCOSH: A novel single-head FCOS for faster object detection in autonomous-driving systems
by: Saad Mboutayeb, et al.
Published: (2024-03-01) -
Implementation of Driving Cycles Based on Driving Style Characteristics of Autonomous Vehicles
by: Xucheng Duan, et al.
Published: (2022-06-01) -
Autonomous Driving of Mobile Robots in Dynamic Environments Based on Deep Deterministic Policy Gradient: Reward Shaping and Hindsight Experience Replay
by: Minjae Park, et al.
Published: (2024-01-01) -
Augmenting CCAM Infrastructure for Creating Smart Roads and Enabling Autonomous Driving
by: M. Jalal Khan, et al.
Published: (2023-02-01)