Enhanced urban driving scene segmentation using modified UNet with residual convolutions and attention guided skip connections
Abstract Autonomous vehicles heavily rely on precise scene understanding to ensure safe navigation. These vehicles house an array of sophisticated sensors and advanced technologies, like computer vision and artificial intelligence, to navigate complex and unpredictable real-world driving scenarios....
Saved in:
| Main Authors: | Siddhant Arora, Ahaan Banerjee, Nitish Katal |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-08-01
|
| Series: | Discover Artificial Intelligence |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s44163-025-00455-x |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Axial-UNet++ Power Line Detection Network Based on Gated Axial Attention Mechanism
by: Ding Hu, et al.
Published: (2024-12-01) -
Res-ECA-UNet++: an automatic segmentation model for ovarian tumor ultrasound images based on residual networks and channel attention mechanism
by: Shushan Wei, et al.
Published: (2025-05-01) -
Swin-ReshoUnet: A Seismic Profile Signal Reconstruction Method Integrating Hierarchical Convolution, ORCA Attention, and Residual Channel Attention Mechanism
by: Jie Rao, et al.
Published: (2025-07-01) -
Single level UNet3D with multipath residual attention block for brain tumor segmentation
by: Agus Subhan Akbar, et al.
Published: (2022-06-01) -
GCBAM-UNet: Sun Glare Segmentation Using Convolutional Block Attention Module
by: Nabila Zrira, et al.
Published: (2024-12-01)