Lightweight Transformer with Adaptive Rotational Convolutions for Aerial Object Detection

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...

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Bibliographic Details
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:
lightweight vision transformer
oriented object detection
semi-supervised learning
rotational invariance
pseudo-labeling
adaptive rotational convolution
Online Access:https://www.mdpi.com/2076-3417/15/9/5212
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