In these "Lightweight" (LS) models, the following components are typically highlighted in the full papers:
This paper introduces a lightweight model designed for underwater vehicles, utilizing Region Scaling (RS) loss and self-attention mechanisms to improve small-object detection in complex environments.
Reduces parameters and FLOPs while maintaining feature extraction quality.
Published in the IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , this paper focuses on remote sensing and landslide detection using a modified YOLOv5/v10-style architecture. Full Text Access: Available via IEEE Xplore.
Based on your search for "LS Models (10)", there are several recent publications that match this technical profile:
Replaces standard loss functions to better handle small or multi-scale objects.
Integrated into the neck or head of the network to capture global context without the heavy computational cost of standard transformers.