YOLORemote: Advancing Remote Sensing Object Detection by Integrating YOLOv8 With the CE-WA-CS Feature Fusion Approach

The rapid development iteration of YOLO models has spurred extensive research into specialized adaptations tailored for remote sensing object detection (RSOD). Typically, these adaptations involve modifying specific YOLO versions to excel in dataset-specific benchmarks. Such efforts primarily focus...

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Bibliographic Details
Main Authors: Ruihan Bai, Guanghan Song, Qiang Wang
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10896792/
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