Gas extraction is an important measure for coal mine gas disaster control. Its effect is closely correlated to the drilling depth. The existing methods usually determine the drilling depth by manually counting the number of drill pipes, and the number of
The enhancements in the proposed algorithm include several key modifications. Firstly, within the feature extraction layers, a designed MFB module is integrated to effectively broaden the network's receptive field. Next, deformable convolutions are introduced in the feature fusion layers to bolster the...
The class is designed to work with the YOLOv8 object detection model and supports ReID only if enabled via args. """def__init__(self, args, frame_rate=30):"""Initialize YOLOv8 object with ReID module and GMC algorithm."""# 调用父类的初始化方法super().__init__(args, frame_rate)#...
et al. Correction: ODD-YOLOv8: an algorithm for small object detection in UAV imagery. J Supercomput 81, 384 (2025). https://doi.org/10.1007/s11227-024-06829-9 Download citation Published09 January 2025 DOIhttps://doi.org/10.1007/s11227-024-06829-9 Share this article Anyone you share ...
However, object detection from UAV images has numerous challenges, including significant variations in the object size, changing spatial configurations, and cluttered backgrounds with multiple interfering elements. To address these challenges, we propose SOD-YOLO, an innovative model based on the YOLOv8 ...
Yolov8 源码解析(二十五) YOLOv8 - Int8-TFLite Runtime Welcome to the YOLOv8 Int8 TFLite Runtime for efficient and optimized object detection project. This REA
而Mask R-CNN在此基础上进一步增加了对目标的分割能力,使得在复杂背景的体育场景中也能准确识别和分割目标。另一方面,基于Transformer的DETR(Detection Transformer)模型摒弃了传统的锚点和NMS步骤,通过全局推理和直接集成的端到端框架,在体育赛事目标检测上展示了新的可能。
In the task of visual object detection for autonomous driving, several challenges arise, such as detecting densely clustered targets, dealing with significant occlusion, and identifying small-sized targets. To address these challenges, an improved YOLOv8 algorithm for small object detection in autonomous...
We look forward to seeing your ideas in action and appreciate your commitment to advancing object detection technology. Let's continue to grow and innovate together in this exciting open-source journey. Happy coding! 🚀🌟 .\yolov8\docs\build_docs.py ...
In recent years, the You Only Look Once (YOLO) series of object detection algorithms have garnered significant attention for their speed and accuracy in real-time applications. This paper presents YOLOv8, a novel object detection algorithm that builds upon the advancements of previous iterations, ...