Unmanned aerial vehicle (UAV) image object detection has extensive applications across both civilian and military domains. However, the traditional YOLOv8
本篇内容:芒果YOLOv8改进:写作篇:新增YOLOv8实验对比COCOmAP指标,即插即用,输出自定义数据集中small、medium、large大中小目标的mAP值,适用于自定义数据集(内附源代码) 推荐一个《YOLOv8改进专栏》链接 如下: 全新芒果YOLOv8改进专栏 | 专栏目录:目前已有150+篇内容,内含各种Head检测头、标签分配策略、损失函数L...
Search before asking I have searched the YOLOv8 issues and discussions and found no similar questions. Question I understand that it is always preferrable to have many hundrets or even better thousands of examples per class in the traini...
Breadcrumbs YOLOv8 /cfg / SmallObj.yamlTop File metadata and controls Code Blame 53 lines (45 loc) · 2.13 KB Raw # Ultralytics YOLO 🚀, GPL-3.0 license # YOLOv8 object detection model with P3-P5 outputs. For Usage examples see https://docs.ultralytics.com/tasks/detect # Parameters...
The CPDD-YOLOv8 is proposed to improve the performance of small object detection. Firstly, we propose the C2fGAM structure, which integrates the Global Attention Mechanism (GAM) into the C2f structure of the backbone so that the model can better understand the overall semantics of the images....
To address the challenges, this article proposes a small object detection based on improved YOLOv8 for airport scene images in hazy weather (ADH-YOLO). Firstly, this article constructs HASS1, HASS2, and HRSOD hazy datasets based on the HAZERD method. We find that YOLOv8 which is anchor-...
UAV-YOLOv8: A Small-Object-Detection Model Based on Improved YOLOv8 for UAV Aerial Photography Scenarios Unmanned aerial vehicle (UAV) object detection plays a crucial role in civil, commercial, and military domains. However, the high proportion of small objec... G Wang,Y Chen,P An,... -...
Aiming at the problems of high model complexity and poor detection effect of UAV object detection algorithm, a small-object-detection model based on improved YOLOv8 is proposed. First, the Diverse Branch Block generalized module component is used in the Backbone network, which can improve the perf...
Meanwhile, existing methods present challenges in accurate detection when facing small and densely arranged underwater targets. To address these issues, we propose a new neural network model, YOLOv8-LA, for improving the detection performance of underwater targets. First, we design a Lightweight ...
To bridge these gaps, we present Prior-YOLO, a novel modification of YOLO v8, marked by advanced network structure and refined inference processes. This adaptation includes a dedicated head for small object detection and a new neck component. We have also curated a custom dataset, particularly ...