FlexiNet: An Adaptive Feature Synthesis Network for Real-Time Ego Vehicle Speed Estimation
Ego vehicle speed estimation is critical for autonomous driving and advanced driver-assistance systems (ADAS), but traditional methods often fail in accuracy and computational efficiency under dynamic conditions. To address these challenges, we propose FlexiNet, a novel adaptive feature synthesis ne...
Saved in:
| Main Authors: | Abdalrahaman Ibrahim, Kyandoghere Kyamakya, Wolfgang Pointner |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10969778/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Commonly used methods to monitor driver’s drowsiness and fatigue with a focus on the interior camera
by: Filip Kotas, et al.
Published: (2025-06-01) -
Developing a Machine Intelligence Quotient (MIQ) for evaluating autonomous vehicle intelligence: a conceptual framework
by: Mehdi Cina, et al.
Published: (2024-10-01) -
Road Traffic Gesture Autonomous Integrity Monitoring Using Fuzzy Logic
by: Kwame Owusu Ampadu, et al.
Published: (2024-12-01) -
The Impact of Rain on Image Quality From Sensors on Connected and Autonomous Vehicles
by: Tim Brophy, et al.
Published: (2025-01-01) -
Emerging Decision-Making for Transportation Safety: Collaborative Agent Performance Analysis
by: Jack Maguire-Day, et al.
Published: (2025-01-01)