基于Gentle Adaboost的气密性检测系统

差压法气密性检测易受外部因素与预设参数影响。针对问题基于集成学习建立气密性检测系统,包含传感器终端数据采集系统、人机交互界面,并用最小二乘法对传感器进行线性拟合,利用Gentle Adaboost算法寻找每轮迭代中最佳弱分类器并更新下一轮样本权重,通过集成数轮迭代中最佳弱分类器组成强分类器,对被测物的气密性能进行判断。实验结果表明:所提系统在气密性检测中的准确度、精确度与召回率皆优于传统方法与单一分类模型,准确度达到99.8%,能有效克服外部因素对检测结果的影响,提高了差压法气密性检测的准确性与稳定性。

Journey Through Zhejiang: A Tapestry of Heritage and Innovation

The moment we stepped off the plane at the Hangzhou airport,the gentle embrace of Zhejiang’s climate welcomed us,setting the stage for an extraordinary exploration of the heart of eastern China.As a journalist from Myanmar representing China Report ASEAN,my journey unfolded with the prestigious 2023 Panda Cup for Foreign Students Essay Contest awards ceremony,where a global tapestry of talent revealed itself.

A Hidden Gem Called Changdao Breathtaking scenery and the islanders’commitment to sustainable living

Changdao Island,a hidden gem in east China’s Shandong Province,features breathtaking nature.As the sun cuddles the horizon,the island’s azure sky provides a flawless backdrop to an exquisite panorama.Jagged cliffs carved by centuries of endless waves stand guard along the shoreline,their rocky silhouettes seemingly frozen in time,summoning ancient majesty.Against this dramatic backdrop,flocks of seagulls take flight,their ivory wings catching the golden hues of the sun,creating an enchanting ballet in the sky.The air is filled with the gentle cries of these graceful birds,enhancing the island’s serenity.This harmonious blend of nature’s elements,from the sapphire sea to the towering cliffs and the mesmerizing flight of seagulls,makes Changdao Island an artistic masterpiece painted by the hand of mother nature herself.

《夏洛的网》中的“说”

必备好词一、轻声“说”1.whisper低声说出(常指耳语、窃窃私语)2.murmur/mutter喃喃自语(多指别人不易听到的低语)3.moan/groan/complain/grumble抱怨着说4.mumble/grunt咕哝5.gossip(对别人的隐私)说长道短6.breathe低声说7.sigh叹着气说8.in a soft/gentle/mild tone/voice用温柔的语气说9.in a whisper低声说。

Remarks of CAFIU President Ji Bingxuan at the Opening Ceremony of the Third Dialogue on Exchanges and Mutual Learning among Civilisations and the First World Conference of Sinologists

Your Excellency Vice-President Han Zheng,Your Excellency Simplice Mathieu Sarandji,Your Excellency Alice Lau Kiong Yieng,Distinguished guests,ladies and gentlemen,Friends,Good Afternoon!Today,representatives from around the world gather in Beijing to celebrate the Third Dialogue on Exchanges and Mutual Learning among Civilisations and the First World Conference ofSinologists.First of all,on behalf of the host of this event,the Chinese Association for International Understanding,please allow me to express our warm welcome and heartfelt thanks to all our friends and guests who attend this event.

Remarks of Chinese Vice-President Han Zheng at the Third Dialogue on Exchanges and Mutual Learning among Civilisations and the First World Conference of Sinologists

Distinguished guests,Ladies and gentlemen,Friends,I'm delighted to join representatives of various countries in Beijing for the Third Dialogue on Exchanges and Mutual Learning among Civilisations and the First World Conference of Sinologists.President Xi Jinping highly values exchanges and mutual understanding amongcivilisations.

Speech by Ji Bingxuan, Vice-Chairperson of the Standing Committee of the 13th National People's Congress and President of the Chinese Association for International Understanding

Distinguished delegates,Ladies and gentlemen,Friends,It gives me great pleasure to gather with you in Tunisia, the Pearl of the Mediterranean Sea, to launch the dialogues on exchanges and mutual learning among civilisations, boost mutual learning and enhance the deep friendship between China and Tunisia.

Address by Ji Bingxuan,Vice-Chairperson of the Standing Committee of the 13th National People's Congress of China and President of the Chinese Association for International Understanding(CAFIU)

Distinguished guests,Ladies and gentlemen,friends,I feel so delighted to meet with all of you on this beautiful autumn day in the central plain of China while attending the Third Silk Road NGO Cooperation Network Forum and jointly contributing to people-to-people exchanges and cooperation under the Belt and Road Initiative.

Address by Ji Bingxuan,Vice-Chairperson of the Standing Committee of the 13th National People's Congress of China and President of the Chinese Association for International Understanding

Distinguished guests,Ladies and gentlemen,friends:Good morning!It is a great pleasure to join all of you in my hometown,Henan Province,to attend the opening ceremony of the Civilisation Lecture.As the cradle of the Chinese civilisation,Henan was endowed with numerous historic treasures.

Double Delight China’s ‘Super Golden Week’ brings lively tapestry of tourism

Travelling in China,especially during the annual National Day holiday,also known as Golden Week,offers an unmissable spectacle-the travellers themselves.This time of year,bathed in the gentle embrace of early autumn,boasts delightful weather and offers the gift of an extended holiday,beckoning people outdoors.With China’s vast population,as people from all walks of life set forth on their trips,the fascinating panorama of bustling crowds becomes an integral part of the travel experience.

长脉冲可调脉宽Gentle YAG 1064nm激光治疗颌面部血管瘤113例效果评估

目的:长脉冲可调脉宽GentleYAG1064nm激光是新问世的医疗激光设备,探讨用其治疗颌面部血管瘤113例,对其效果进行评估。方法:自2005年4月至8月,应用美国Candela激光公司生产的GentleYAG1064nm激光治疗口腔颌面部血管瘤113例。采用最小激光凝固剂量方法,激光能量参数为170～240J/cm2,光斑直径1.5mm,脉宽30￣60ms。激光脉冲前动态冷却(DCD)10～20次,脉冲后DCD10～15次。疗程1￣2个(9例为2个疗程,104例1个疗程)。随访3￣6个月,随访率96%。结果:全部病灶清除85例,占75.22%;有效清除(50%￣75%病灶清除)28例,占24.78%;部分清除(病灶清除<50%)0例,无效率为0。伴色素沉着11例(9.73%),色素脱失2例(1.77%),色素改变均自然恢复,历时4￣5个月。瘢痕7例,占6.19%。结论:长脉冲GentleYAG1064nm激光小剂量照射是口腔颌面部血管瘤治疗的有效手段,具有起效快、疗程短、副作用小的显著优点,宜推广应用。

基于Gabor小波的火灾烟气识别新方法

研究提出一种基于Gabor小波的火灾烟气模型,以提高基于视频图像的火灾烟气检测的准确性。本文采用混合高斯模型与色度方差相结合的方法定位火灾烟气目标区域,并基于Gabor小波对烟气纹理及边缘特征进行描述,从而提出烟气变化能量模型与方向角分布模型来分析纹理变化的动态性质。最后采用Gentle Boosting设计分类器对模型特征进行分类与匹配,并实现在训练的同时进行最优特征选择。与传统方法相比,基于本文方法的火灾烟气检测在降低漏报率与误报率方面拥有更好的性能。

基于改进AdaBoost算法的人耳检测与跟踪

人耳检测是人耳识别系统的第一个环节.在比较已有的人耳检测方法的基础上,介绍了一种复杂背景下的快速人耳检测与跟踪的方法.该方法主要分为两个阶段,离线级联分类器训练阶段和在线检测阶段.在离线训练阶段,首先结合人耳轮廓清晰,凹凸有致的特点,采用扩充后的haar-like型特征,依最近邻法则构造出弱分类器空间,然后根据经验选择GAB算法训练出强分类器,最后将多个强分类器级联成多层人耳检测器.在线检测阶段,为提高检测率,本文采用了调整分类器阈值和缩放检测子窗口的策略.最终检测器在CAS-PEAL人脸库上测试,检测率达到98%以上;在PⅣ1.7GHz的PC上对普通CMOS摄像头输入的320×240dpi视频进行人耳跟踪,速度可达6～7fps.实验结果表明,本文的人耳检测方法具有较好的实时性和一定的鲁棒性.

移动摄像机环境下基于特征变换和SVM的分级行人检测算法

本文提出了一种应用于单目移动摄像机的基于特征变换和支持向量机(Support Vector Machine,简称SVM)的coarse-to-fine行人检测方法.首先,用查找表(Look-Up Table,简称LUT)Gentle AdaBoost Cascade训练一个粗级的行人检测器.接着把粗级的行人检测器的每一段分别作为一个特征,并用能通过粗级行人检测器的正负样本来训练基于SVM的精密级行人检测器.最后,采用基于颜色和空间信息的时序分析方法进一步提高行人检测率和降低误报率.从实验结果可以看出我们算法的高效性.

长脉冲1064nm Gentle YAG激光治疗皮肤血管瘤259例临床分析

目的:观察长脉冲1064nm Gentle YAG激光治疗皮肤血管瘤的临床疗效和不良反应。方法:应用长脉冲1064nm Gentle YAG激光治疗皮肤血管瘤患者259例,能量密度110～240J/cm2,光斑直径3mm,脉宽20～50ms。共治疗1～6次,间隔时间6～8周。结果:完全治愈20例(占7.72%),基本治愈166例(占64.09%),显效56例(占21.62%),有效17例(占6.56%),无效0例。治疗1～4次后平均病灶清除率分别为42.10%,67.18%,74.95%及86.13%,疗效稳步上升。治疗后出现色素性改变47例(18.15%),均在数月至半年后恢复,遗留浅表性瘢痕9例(3.47%),增生性瘢痕2例(0.77%)。结论:长脉冲1064nm Gentle YAG激光治疗皮肤血管瘤疗效高,起效快,不良反应低,可在临床推广使用。

一种树形结构的实时道路车辆识别方法

针对实时道路车辆识别是车辆计算机辅助驾驶、自主导航以及主动安全的关键技术,给出了一种基于树形结构的车辆识别方法。该方法采用Haar-like特征来表达车辆特征,选择Gentle AdaBoost算法训练出强分类器,最后将多个强分类器组合成树形结构。通过建立样本库,对车辆识别分类器进行了训练,并对分类器的性能进行了实验。结果表明:对750个目标车辆进行识别,识别率为74.4%,识别时间为34.4 ms。说明树形结构的车辆识别方法具有较好的实时性和一定的鲁棒性。

改进的快速行人检测方法

行人检测在视频监控以及智能车系统中有着广泛的应用前景,为了能够更有效地检测行人,将人脸检测中级联检测框架引入行人检测中,并对其进行改进,采用Gentle AdaBoost算法进行分类器训练,以提高训练效率,同时在训练前引入了特征预筛选,以减少训练时间和系统开销。实验表明,改进后的方法训练时间短,检测精度高,同时具有较快的检测速度。

采用Gentle AdaBoost和嵌套级联结构的实时人脸检测

本文提出一个基于Gentle AdaBoost和嵌套级联结构(Nesting Cascade Structure)的快速人脸检测器。采用嵌套级联结构并在训练过程中剔除前级节点分类器已使用过的特征,解决了经典的AdaBoost级联分类器因各节点分类器独立训练导致不同节点之间特征相同的弱分类器大量存在而影响检测速度的问题,提高了人脸检测速度。采用Gentle AdaBoost算法训练节点分类器以提高各节点分类器的泛化能力,进一步减少嵌套级联结构中弱分类器的个数。实验结果表明本文所提出的人脸检测算法大幅度减少了级联分类器所需的弱分类器个数,使检测的速度得到明显的提高,在CIF(352×288)格式的视频上达到每帧8毫秒的检测速度,优于现有的人脸检测算法,而且检测的准确性也比现有的人脸检测算法略有提高。

基于Gentle Adaboost的行人检测

行人检测是物体检测领域的一大难点。为了更加快速地检测行人,将人脸检测中Boosted Cascade算法应用到行人检测中,并对其进行了改进,即先利用加权平均矢量投影的方法将高维的梯度直方图特征化为1维,再利用lookup table进行概率密度估计,从而将Gentle Adaboost成功地应用于行人检测。实验表明,该方法不仅训练时间短、检测速度快,而且检测精度接近目前的最佳水平。

Boosting在火灾识别中的应用研究

提出一种通过计算机图像识别火灾的新方法。首先根据亮度定位可疑火灾区域,对该区域中像素点提取亮度变化率及火焰面积变化率等特征,并提出一种新的谱值特征,以消除规则闪动的光源带来的干扰。之后,采用Gentle Boosting算法设计分类器,在训练的同时进行最优特征选择,实现了对特征空间的降维及分类。最后,实验给出了在多种环境下的识别结果及对细小火苗的定位结果,表明了方法在识别精度与计算时间上的优势。