以下是我们的创新点:🔍 首先,我们结合特征分立合并的思想,对YOLOv7网络模型中的MPConv模块进行了改进。通过这种方式,我们减少了特征处理过程中的损失,并通过实验找到了放置改进MPConv模块的最佳位置。🔍 其次,为了解决小目标检测中的漏检问题,我们引入了ACmix注意力模块。这不仅增加了网络对小尺度目标的敏感度,还...
YOLOv7在这方面做了很大的改进。我们引入了ACmix注意力模块,这个模块能增加网络对小尺度目标的敏感度,同时降低噪声的影响。它结合最大池化层与多头自注意力机制,能够在复杂背景下提高特征提取能力。这样处理后的图像,小目标的细节信息更加突出,模型的鲁棒性也更强了。 💀改良损失函数 YOLOv7在损失函数上也进行了...
The hybrid attention module ACmix is added to the backbone network of the YOlOv7 basic framework to enhance the sensitivity of the network to small target detection and improve the detection accuracy of small vessels. Adding global attention mechanism (NAMAttention) and Partial convolution (PConv)...
针对YOLOv7原始主干网络非线性特征融合不足的问题,运用Res3Unit结构重构主干网络,增强了网络捕获非线性特征的能力。 引入混合注意力机制模块ACmix,该模块可作为即插即用组件,安装在主干网络特定层后,增强了对车辆目标的注意力,有效抑制了背景和其他目标的干扰。 针对小目标在远距离视角下容易漏检的问题,通过在特征融合...
8.改进YOLOv5系列:8.增加ACmix结构的修改,自注意力和卷积集成 7.改进YOLOv5系列:7.修改DIoU-NMS,SIoU-NMS,EIoU-NMS,CIoU-NMS,GIoU-NMS 6.改进YOLOv5系列:6.修改Soft-NMS,Soft-CIoUNMS,Soft-SIoUNMS 5.改进YOLOv5系列:5.CotNet Transformer结构的修改 4.改进YOLOv5系列:4.YOLOv5_最新MobileOne...
为解决高分辨率遥感图像中舰船识别准确率低的问题,提出了一种改进的YOLOv7-OBB舰船识别方法.引入定向检测框OBB(oriented bounding box)和KLD损失,可有效解决舰船密集排列和比例细长且方向任意所产生的漏检问题,在提高定位精度的同时保留了船只的目标方向信息;在YOLOv7基础框架的主干网络加入混合注意力模块ACmix,加强网络...
The model effectively optimizes the detection performance of display defects, especially small target defects, by integrating GhostNetV2 modules, Acmix attention mechanisms, and NGWD (Normalized Gaussian Wasserstein Distance) Loss. At the same time, it reduces the parameter size of the network model ...
Simultaneously, the integration of self-attention and convolutional mix modules (ACmix) was applied to the newly added small target detection layer, enabling the capture of additional feature information through the convolutional and self-attention channels within ACmix. Furthermore, the feature ...
First, the ACmix attention mechanism is added after the backbone network of YOLOv7 algorithm, and second, drawing on the ideas of Soft-NMS algorithm and DIOU-NMS algorithm, CHSD-NMS algorithm is proposed, which improves the base NMS algorithm by softening the strategy of eliminating the ...
ACmix (a hybrid model combining the advantages of self-attentiveness and convolution) is also included, with ACmix module improved. The improved ACmix module has the objectives of enhancing feature extraction capability of backbone network and accelerating network convergence...