A test object with a line width less than 10 nm for scanning electron microscopy

Data are given on the test object for scanning electron microscopy in which the components (ridges) are of trapezoidal profile and have large angles of inclination for the side walls. The width of the top surface of a projection is less than 10 nm. Methods have been developed for measuring such dimensions of test objects on standard scanning electron microscopes. __________ Translated from Izmeritel'naya Tekhnika, No. 8, pp. 20–23, August, 2008.     

基于YOLO的钢缆表面损坏检测

为了解决检测钢缆表面损坏时检测设备资源有限、时间过长等问题,将深度学习的先进技术以及卷积神经网络(CNN)应用于钢缆表面损坏检测.提出了一种基于YOLO的缺陷检测网络模型,将GhostNet融入主干网络,并基于ShuffleNet及注意力机制提出了新的特征提取模块(ShuffleC3),再对Head部分进行剪枝改进.实验结果表明,改进后网络相比基线YOLOv5s的平均精度提高1.1%,参数量和计算量分别降低了43.4%和31%,模型大小减少了42.3%.可以在降低网络计算成本的同时,保持较高的识别精确度,更好地满足了对钢缆材料表面损坏检测的要求.     

改进YOLOv8的水面小目标检测算法

针对水面目标检测中的噪声干扰和小目标的漏检问题,提出一种改进YOLOv8的水面小目标检测算法YOLOv8-WSSOD (YOLOv8-water surface small object detection).首先,为降低水面复杂环境在主干网络下采样过程中产生的噪声干扰,提出基于BiFormer双层路由注意力机制构建的C2fBF (C2f-BiFormer)模块,在特征提取过程中保留细粒度的上下文特征信息;其次,针对水面小目标的漏检问题,新增一个更小的检测头,提升网络对小目标的感知力,并在Neck端引入GSConv和Slim-neck,减轻模型复杂度并保持精度;最后,使用MPDIoU损失函数解决CIoU损失函数的局限性,以提高模型检测准确率.实验结果表明,相较于原始YOLOv8算法,该算法在水面小目标上平均准确率mAP@0.5提升了4.6%, mAP@0.5:0.95提升了2.2%,并且改进后的算法检测速度达到86f/s,能有效实现对水面小目标快速、准确的检测.     

基于区分对象对的不完备决策表求核

在差别矩阵的基础上,针对不完备决策表提出了基于差别矩阵的区分对象对集定义,并证明求不完备决策表的核可以转化到求基于差别矩阵的区分对象对集上。在此基础上,提出了一种基于区分对象对的不完备决策表求核算法,该算法的时间复杂度为：[max{O(|C||U||Upos|),O(K|C||U|)}],优于同类算法的时间复杂度;用实例说明了新算法的有效性。     

The Skeptical Explorer: A Multiple-Hypothesis Approach to Visual Modeling and Exploration

The primary intent of this work is to present a method for sequentially associating three-dimensional surface measurements acquired by an autonomous exploration agent with models that describe those surfaces. Traditional multiple-viewpoint registration approaches are concerned only with finding the transformation that maps data points to a chosen global frame. Given a parts-based object representation, and assuming that the view correspondence can be found, the problem of associating the registered data with the correct part models still needs to be solved. While traditional approaches are content to group segmented data sets that geometrically overlap one another with the same part, there are cases where this causes ambiguous situations. This paper addresses the model-data association problem as it applies to three-dimensional dynamic object modeling. By tracking the state of part models across subsequent views, we wish to identify possible events that explain model-data association ambiguities and represent them in a Bayesian framework. The model-data association problem is therefore relaxed to allow multiple interpretations of the object's structure, each being assigned a probability. Rather than making a decision at every iteration about an ambiguous mapping, we look to the future for the information needed to disambiguate it. Experimental results are presented to illustrate the effectiveness of the approach.     

基于B/S结构的服装销售管理系统的设计与实现

针对现有服装销售管理的现状及信息化需求,研究了基于B/S结构的服装销售管理系统,并利用asp加以实现。通过三层结构实现了系统的原型设计,介绍了基于B/S结构的服装销售管理系统的体系结构、功能及系统实现的关键技术。     

花朵图像自动提取方法研究

采用改进的主动轮廓模型算法,实现从蝴蝶兰花簇图像中提取单个花朵图像,为自动识别蝴蝶兰的生长状态奠定基础。首先利用改进的骨架算法和轮廓重生算法,生成蝴蝶兰花簇的初始轮廓;然后利用含有形状能量的主动轮廓模型进行轮廓的演化,使其更接近真实的蝴蝶兰花簇边缘,最后根据蝴蝶兰花蕊位置获得相应的蝴蝶兰花朵。实例验证和比对实验结果表明,该模型能够较好的分割和提取蝴蝶兰花簇中单个花朵,并具有较强的抗噪能力。利用该方法,可以较好的提取蝴蝶兰花簇中的单个花朵,与人工提取效果进行比对,正确率达到了91.5%。     

基于遥感影像中电磁特性的地物提取方法

电磁特性数据是电子信息装备内场仿真试验不可或缺的数据资源,为了克服传统电子信息装备仿真试验中的电磁特性数据获取方法的不足,提出了从遥感影像中大批量获取大区域范围的电磁特性数据的新方法.首先依据不同地物的电磁特性规律对某一地域的地物进行了分类,从多尺度分割概念和基于异质性最小的区域合并算法两个方面.深入研究了针对地物分类的面向对象多尺度分割算法,并结合实践对算法进行了应用.由于遥感影像的真实性.保证了电磁特性数据提取的准确性与可靠性,实践证明此研究为大批量获取电磁特性数据提供了一种有效的方法和思路.     

基于层次分析法的城市反空袭防护目标选择

通过对防护目标的选定因素分析,城市反空袭防护目标指标体系包括目标层、准则层及措施层.利用层次分析法(AHP)法选定城市反空袭中的防护目标,形成数据表、建立并求解判断矩阵及一致性检验,以获得选择最优保护目标的排序权重.经实际运用,所建立的指标体系和方法更有利于合理、科学地选择防护目标.     

变压器三维设计系统中三维实体与非投影视图关联设计的实现

介绍了在变压器三维设计系统中将三维实体与非投影视图实现属性关联的方法.