Ls Models (10) Mp4 100%

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.

Replaces standard loss functions to better handle small or multi-scale objects. Ls Models (10) mp4

Reduces parameters and FLOPs while maintaining feature extraction quality. Published in the IEEE Journal of Selected Topics

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. While based on YOLOv8, this "LS" (Lightweight and

Available for request or viewing on ResearchGate .

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