为了应对这些问题,对YOLOV8的结构进行改进,改进后的部分在图3中以红色虚线框表示。 图3改进的YOLOV8算法结构Fig.3Improvement of YOLOV8 algorithm structure 2.2 主干部分引入动态稀疏注意力 注意力机制能够有效捕获全局和局部的关联性,通过计算和强调...
yolov8不使用预训练权重训练 The networkstructure of these models is constant, but the modules and con-volution kernels are scaled, which alters the complexity and sizeof each model.(这些模型的网络结构是恒定的,但模块和卷积核被缩放,这改变了每个模型的复杂性和大小。) YOLOv5 ✅backbone:Focus layer...
图5 Fire-YOLOv8整体网络结构 Fig. 5 Fire-YOLOv8 Overall Network Structure 3 实验及结果分析 3.1 构建数据集 3.1.1数据集采集 为了解决现有烟火数据集存在的场景单一、类火类烟物干扰、小目标难以识别等问题,本实验运用爬虫技术收集各大网站上的火灾视...
This is fed to the neural network. Here, we have provided one example, but in the real world, many images are provided as the training set. These images are converted into vectors for each corresponding image. Since this is a supervised problem, the X_train and y_train will be the imag...
Graph-based Model Representation: ONNX represents models as computational graphs. This graph-based structure is a universal way of representing machine learning models, where nodes represent operations or computations, and edges represent the tensors flowing between them. This format is easily adaptable...
Furthermore, we replaced the network structure of YOLOv8 with a weighted bidirectional feature pyramid network to achieve weighted feature fusion, aiming to improve model performance and reduce computational complexity. Finally, we replaced the IOU loss function design in the YOLOv8 model with Wise ...
The YOLOv8 network structure is shown in Fig. 1. Download: Download high-res image (471KB) Download: Download full-size image Fig. 1. YOLOv8 network architecture. a) CSPDarknet53 network used by Backbone; b) FPN + PAN pyramid structure used by Neck; c) decoupled header structure used ...
采用 Mosaic数据增强方法的思想是随机使用4张不同图 像,将其随机拼接成一张大的图像,可以增加训练集的多样性 图1 YOLOv8网络结构图 Fig.1YOLOv8networkstructurediagram 和难度,有助于提高目标检测模型的泛化能力. 在网络训练前,自适应锚框通过学习的方式自动计算出最 适合输入图像的锚框参数,不需要手动设置.这种...
图1模型结构示意图Fig.1Schematic of model structure 1.2 重构主干网C2f模块处理图像位置关系 在露天矿区,由于无人驾驶矿卡车的车载摄像头经常受到扬尘和颗粒物等粉尘的遮挡,加上空气中弥漫着大量尘土,导致摄像头捕捉到的图像模糊;夜间矿区照明设施不充...
Figure 1. YOLOv8 network structure diagram. The feature extraction network mainly extracts individual scale features from images created by the C2f and SPPF modules. The C2f module reduces the network by one convolutional layer based on the original C3 module, making the model more lightweight...