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.

Available for request or viewing on ResearchGate .

In these "Lightweight" (LS) models, the following components are typically highlighted in the full papers:

Reduces parameters and FLOPs while maintaining feature extraction quality.

While based on YOLOv8, this "LS" (Lightweight and Scalable) variant is highly cited for its use of Multi-Scale Ghost Convolution (MSGConv) and efficiency gains of up to 55% FPS. Full Text Access: View the full paper on ResearchGate . Key Technical Features of LS-Models