Lightweight Transformer with Adaptive Rotational Convolutions for Aerial Object Detection
Oriented object detection in aerial imagery presents unique challenges due to the arbitrary orientations, diverse scales, and limited availability of labeled data. In response to these issues, we propose RASST—a lightweight Rotationally Aware Semi-Supervised Transformer framework designed to achieve...
Saved in:
| Main Authors: | Sabina Umirzakova, Shakhnoza Muksimova, Abrayeva Mahliyo Olimjon Qizi, Young Im Cho |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/9/5212 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
SPEMix: a lightweight method via superclass pseudo-label and efficient mixup for echocardiogram view classification
by: Shizhou Ma, et al.
Published: (2025-01-01) -
Lightweight Deep Learning Model for Fire Classification in Tunnels
by: Shakhnoza Muksimova, et al.
Published: (2025-02-01) -
RL-Cervix.Net: A Hybrid Lightweight Model Integrating Reinforcement Learning for Cervical Cell Classification
by: Shakhnoza Muksimova, et al.
Published: (2025-02-01) -
Lightweight Fire Detection in Tunnel Environments
by: Shakhnoza Muksimova, et al.
Published: (2025-03-01) -
GazeCapsNet: A Lightweight Gaze Estimation Framework
by: Shakhnoza Muksimova, et al.
Published: (2025-02-01)