化学杂交剂1-芳基-1,4-二氢-4-氧(硫)哒嗪衍生物的二维结构——选择性雄性不育活性关系研究

报道了结构框架模型法与模式识别相结合,实现化学杂交荆的选择性雄性不育活性分类和预测的计算机实验结果。此法可用于辅助筛选和设计新的化学杂交剂。     

CAD系统中的汉字处理技术

In this paper, a method of vector chinese character font definition and vector chinese character font library organization is discussed in detail. The paper also describes a commonly used CCP technique for CAD systems in personal computers and working sta     

基于车牌识别的校园车辆出入管理系统研究

面对出入园区机动车辆数量的日益增多,高校校园相关管理部门所采用的传统人工管理方式已经不能满足管理的需要。通过调查,针对当前实际管理中所存在的问题,提出了一种基于车牌自动识别技术的车辆出入管理信息系统,即通过车辆图像信息的采集、车牌定位、字符分割、字符识别等操作完成车牌身份信息的自动提取,最后将获取到的信息存入数据库,通过搜索、查询匹配等模块的处理,实现自动智能管理的要求。通过实验,系统具有较高的识别率,能满足实际应用的需要,具有一定的工程应用价值。     

计算机视觉技术在玉米生产管理中的应用

计算机视觉技术已经广泛应用于农业生产领域。对计算机视觉技术在玉米种子质量检验、玉米品种的识别、玉米粒形的检测、玉米田间杂草的识别等方面的应用做了介绍。     

人脸表情识别中滤波算法的研究

去噪滤波技术是数字图像处理中的一个重要内容,是计算机视觉技术、模式识别、图像数据分析的基础,因而受到广泛的研究;并在人脸识别、表情识别、遥感成像等领域获得广泛的应用。通过对多种去噪滤波算法进行比较,选定了一种改进的二维中值滤波快速算法将其应用到表情识别中,得到较好效果。     

植物叶片智能分析系统的设计

为避免农作物病害智能诊断过程中人为主观因素的影响,客观准确的表达叶片信息,利用数字图像处理技术和农业植保专家知识相结合,设计了适合于大田作物的植物叶片图像处理与分析系统。该系统主要包括植物叶片几何失真校正模块,几何特征计算模块、颜色识别模块以及病害区域识别模块;以校正后非线性失真现象的叶片图像为基础,实现了叶片几何特征值和颜色值的计算,并提取其病斑区域图像。试验结果表明,该方法满足病害智能诊断要求,具有良好的适应性和实用性。     

基于最小阈值法的棉花幼苗识别研究

 面对纯机械式分苗机构经常出现的漏分和多分的问题,本文提出使用基于最小阈值法的图像识别技术对棉花幼苗进行识别和分离。使用了HSV颜色空间内与光照条件无关的H值将RGB真彩色图像转化为灰度图像,以提高图像处理的实时性。基于最小值阈值法,提出一种能够有效地将处于复杂背景下的棉花幼苗茎部图像提取的方法,使用棉花幼苗茎部图像的面积和长宽比等几何信息能有效识别棉花幼苗,并得到棉花幼苗茎部的重心坐标。本文的研究证明了用图像处理中的最小阈值法识别棉花幼苗是可行的。     

Uterine biology in pigs and sheep

There is a dialogue between the developing conceptus (embryo-fetus and associated placental membranes) and maternal uterus which must be established during the peri-implantation period for pregnancy recognition signaling, implantation, regulation of gene expression by uterine epithelial and stromal cells, placentation and exchange of nutrients and gases. The uterus provide a microenvironment in which molecules secreted by uterine epithelia or transported into the uterine lumen represent histotroph required for growth and development of the conceptus and receptivity of the uterus to implantation. Pregnancy recognition signaling mechanisms sustain the functional lifespan of the corpora lutea (CL) which produce progesterone, the hormone of pregnancy essential for uterine functions that support implantation and placentation required for a successful outcome of pregnancy. It is within the peri-implantation period that most embryonic deaths occur due to deficiencies attributed to uterine functions or failure of the conceptus to develop appropriately, signal pregnancy recognition and/or undergo implantation and placentation. With proper placentation, the fetal fluids and fetal membranes each have unique functions to ensure hematotrophic and histotrophic nutrition in support of growth and development of the fetus. The endocrine status of the pregnant female and her nutritional status are critical for successful establishment and maintenance of pregnancy. This review addresses the complexity of key mechanisms that are characteristic of successful reproduction in sheep and pigs and gaps in knowledge that must be the subject of research in order to enhance fertility and reproductive health of livestock species.     

Pattern recognition receptors in equine endotoxaemia and sepsis

Pattern recognition receptors (PRRs) on host cells detect pathogens to activate innate immunity which, in turn, initiates inflammatory and adaptive immune responses. Successful activation of PRRs is, therefore, critical to controlling infections and driving pathogen-specific adaptive immunity, but overactivity of PRRs causes systemic inflammation, which is detrimental to the host. Here we review the PRR literature as it relates to horses and speculate on the role PRRs may play in sepsis and endotoxaemia.     

基于鱼体特征点检测的淡水鱼种类识别

针对传统机器视觉技术对淡水鱼种类进行检测时特征提取过程复杂的问题,该研究提出了基于特征点检测的淡水鱼种类识别方法。以鳊、鳙、草鱼、鲢、鲤5种大宗淡水鱼为对象,构建了淡水鱼特征点检测数据集;以AlexNet模型为基础,通过减小卷积核尺寸、去除局部响应归一化、引入批量归一化、更换损失函数,构建了改进AlexNet模型用于特征点检测;并以特征点为依据提取特征值、构造特征向量,使用Fisher判别分析方法实现了淡水鱼的种类识别。试验结果表明：改进AlexNet模型在测试集上的归一化平均误差的均值为0.0099,阈值δ为0.02和0.03时的失败率F_0.02、F_0.03分别为2.50%和0.83%,具有较好的精准度和误差分布情况;基于该模型和Fisher判别分析的淡水鱼种类识别方法对5种淡水鱼的识别准确率为98.0%,单幅图像的平均识别时间为0.368 s,保证了时效性。由此可知,提出的改进AlexNet模型能实现淡水鱼的特征点检测并具有较高的精度,可为淡水鱼种类识别、尺寸检测、鱼体分割等提供条件,该方法可为淡水鱼自动化分类装置的研发奠定基础。