为提高小麦病害检测精度,实现将模型方便快速部署到移动端,该研究提出了一种基于改进YOLOv8的轻量化小麦病害检测方法。首先,使用PP-LCNet模型替换YOLOv8网络结构的骨干网络,并在骨干网络层引入深度可分离卷积(depthwise separable conv...为提高小麦病害检测精度,实现将模型方便快速部署到移动端,该研究提出了一种基于改进YOLOv8的轻量化小麦病害检测方法。首先,使用PP-LCNet模型替换YOLOv8网络结构的骨干网络,并在骨干网络层引入深度可分离卷积(depthwise separable convolution, DepthSepConv)结构,减少模型参数量,提升模型检测性能;其次,在颈部网络部分添加全局注意力机制(global attention mechanism, GAM)模块,强化特征中语义信息和位置信息,提高模型特征融合能力;然后,引入轻量级通用上采样内容感知重组(content-aware reassembly of features,CARAFE)模块,提高模型对重要特征的提取能力;最后,使用Wise-IoU(weighted interpolation of sequential evidence for intersection over union)边界损失函数代替原损失函数,提升网络边界框回归性能和对小目标病害的检测效果。试验结果表明,对于大田环境下所采集的小麦病害数据集,改进后模型的参数量及模型大小相比原YOLOv8n基线模型分别降低了12.5%和11.3%,同时精确度(precision)及平均精度均值(mean average precision,m AP)相较于原模型分别提高了4.5和1.9个百分点,优于其他对比目标检测算法,可为小麦病害检测无人机等移动端检测装备的部署和应用提供参考。展开更多
Based on inspection data,the authors analyze and summarize the main types and distribution characteristics of tunnel structural defects.These defects are classified into three types:surface defects,internal defects,an...Based on inspection data,the authors analyze and summarize the main types and distribution characteristics of tunnel structural defects.These defects are classified into three types:surface defects,internal defects,and defects behind the structure.To address the need for rapid detection of different defect types,the current state of rapid detection technologies and equipment,both domestically and internationally,is systematically reviewed.The research reveals that surface defect detection technologies and equipment have developed rapidly in recent years.Notably,the integration of machine vision and laser scanning technologies have significantly improved detection efficiency and accuracy,achieving crack detection precision of up to 0.1 mm.However,the non-contact rapid detection of internal and behind-the-structure defects remains constrained by hardware limitations,with traditional detection remaining dominant.Nevertheless,phased array radar,ultrasonic,and acoustic vibration detection technologies have become research hotspots in recent years,offering promising directions for detecting these challenging defect types.Additionally,the application of multisensor fusion technology in rapid detection equipment has further enhanced detection capabilities.Devices such as cameras,3D laser scanners,infrared thermal imagers,and radar demonstrate significant advantages in rapid detection.Future research in tunnel inspection should prioritize breakthroughs in rapid detection technologies for internal and behind-the-structure defects.Efforts should also focus on developing multifunctional integrated detection vehicles that can simultaneously inspect both surface and internal structures.Furthermore,progress in fully automated,intelligent systems with precise defect identification and real-time reporting will be essential to significantly improve the efficiency and accuracy of tunnel inspection.展开更多
Objective:Verrucous epidermal nevus(VEN),seborrheic keratosis(SK),verruca plana(VP),verruca vulgaris(VV),and nevus sebaceous(NS)are common verrucous proliferative skin diseases with similar clinical appearances,often ...Objective:Verrucous epidermal nevus(VEN),seborrheic keratosis(SK),verruca plana(VP),verruca vulgaris(VV),and nevus sebaceous(NS)are common verrucous proliferative skin diseases with similar clinical appearances,often posing diagnostic challenges.Dermoscopy and reflectance confocal microscopy(RCM)can aid in their differentiation,yet their specific features under these tools have not been systematically described.This study aims to summarize and analyze the dermoscopic and RCM features of VEN,SK,VP,VV,and NS.Methods:A total of 121 patients with histopathologically confirmed verrucous proliferative skin diseases were enrolled.Dermoscopy and RCM imaging was used to observe and analyze the microscopic features of these conditions.Results:Under dermoscopy,the 5 diseases displayed distinct characteristics:VEN typically showed gyriform structures;SK was characterized by gyriform structures,comedo-like openings,and milia-like cysts;VP and VV featured dotted vessels and frogspawn-like structures;NS presented as brownish-yellow globules.RCM revealed shared features such as hyperkeratosis and acanthosis across all 5 diseases.Specific features included gyriform structures and elongated rete ridges in VEN;pseudocysts and gyriform structures in SK;evenly distributed ring-like structures in VP;vacuolated cells and papillomatous proliferation in VV;and frogspawn-like structures in NS.Conclusion:These 5 verrucous proliferative skin conditions exhibit distinguishable features under both dermoscopy and RCM.The combination of these 2 noninvasive imaging modalities holds significant clinical value for the differential diagnosis of verrucous proliferative skin diseases.展开更多
文摘为提高小麦病害检测精度,实现将模型方便快速部署到移动端,该研究提出了一种基于改进YOLOv8的轻量化小麦病害检测方法。首先,使用PP-LCNet模型替换YOLOv8网络结构的骨干网络,并在骨干网络层引入深度可分离卷积(depthwise separable convolution, DepthSepConv)结构,减少模型参数量,提升模型检测性能;其次,在颈部网络部分添加全局注意力机制(global attention mechanism, GAM)模块,强化特征中语义信息和位置信息,提高模型特征融合能力;然后,引入轻量级通用上采样内容感知重组(content-aware reassembly of features,CARAFE)模块,提高模型对重要特征的提取能力;最后,使用Wise-IoU(weighted interpolation of sequential evidence for intersection over union)边界损失函数代替原损失函数,提升网络边界框回归性能和对小目标病害的检测效果。试验结果表明,对于大田环境下所采集的小麦病害数据集,改进后模型的参数量及模型大小相比原YOLOv8n基线模型分别降低了12.5%和11.3%,同时精确度(precision)及平均精度均值(mean average precision,m AP)相较于原模型分别提高了4.5和1.9个百分点,优于其他对比目标检测算法,可为小麦病害检测无人机等移动端检测装备的部署和应用提供参考。
文摘Based on inspection data,the authors analyze and summarize the main types and distribution characteristics of tunnel structural defects.These defects are classified into three types:surface defects,internal defects,and defects behind the structure.To address the need for rapid detection of different defect types,the current state of rapid detection technologies and equipment,both domestically and internationally,is systematically reviewed.The research reveals that surface defect detection technologies and equipment have developed rapidly in recent years.Notably,the integration of machine vision and laser scanning technologies have significantly improved detection efficiency and accuracy,achieving crack detection precision of up to 0.1 mm.However,the non-contact rapid detection of internal and behind-the-structure defects remains constrained by hardware limitations,with traditional detection remaining dominant.Nevertheless,phased array radar,ultrasonic,and acoustic vibration detection technologies have become research hotspots in recent years,offering promising directions for detecting these challenging defect types.Additionally,the application of multisensor fusion technology in rapid detection equipment has further enhanced detection capabilities.Devices such as cameras,3D laser scanners,infrared thermal imagers,and radar demonstrate significant advantages in rapid detection.Future research in tunnel inspection should prioritize breakthroughs in rapid detection technologies for internal and behind-the-structure defects.Efforts should also focus on developing multifunctional integrated detection vehicles that can simultaneously inspect both surface and internal structures.Furthermore,progress in fully automated,intelligent systems with precise defect identification and real-time reporting will be essential to significantly improve the efficiency and accuracy of tunnel inspection.
基金supported by the Project of Health Committee of Hunan Province(D202304128868),China.
文摘Objective:Verrucous epidermal nevus(VEN),seborrheic keratosis(SK),verruca plana(VP),verruca vulgaris(VV),and nevus sebaceous(NS)are common verrucous proliferative skin diseases with similar clinical appearances,often posing diagnostic challenges.Dermoscopy and reflectance confocal microscopy(RCM)can aid in their differentiation,yet their specific features under these tools have not been systematically described.This study aims to summarize and analyze the dermoscopic and RCM features of VEN,SK,VP,VV,and NS.Methods:A total of 121 patients with histopathologically confirmed verrucous proliferative skin diseases were enrolled.Dermoscopy and RCM imaging was used to observe and analyze the microscopic features of these conditions.Results:Under dermoscopy,the 5 diseases displayed distinct characteristics:VEN typically showed gyriform structures;SK was characterized by gyriform structures,comedo-like openings,and milia-like cysts;VP and VV featured dotted vessels and frogspawn-like structures;NS presented as brownish-yellow globules.RCM revealed shared features such as hyperkeratosis and acanthosis across all 5 diseases.Specific features included gyriform structures and elongated rete ridges in VEN;pseudocysts and gyriform structures in SK;evenly distributed ring-like structures in VP;vacuolated cells and papillomatous proliferation in VV;and frogspawn-like structures in NS.Conclusion:These 5 verrucous proliferative skin conditions exhibit distinguishable features under both dermoscopy and RCM.The combination of these 2 noninvasive imaging modalities holds significant clinical value for the differential diagnosis of verrucous proliferative skin diseases.
