[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"chains-groupcat":3,"experts-list":4,"experts-coverage":449,"tags-groups":451},[],{"list":5,"total":445,"page":446,"pageSize":447,"totalPages":448},[6,21,35,45,54,64,74,83,92,101,111,125,162,178,206,216,227,239,258,267,280,292,313,325,354,371,390,406,422,433],{"id":7,"name":8,"orgName":9,"school":9,"gender":10,"title":11,"degree":10,"honor":10,"position":10,"researchDirection":12,"intro":13,"province":14,"completeness":15,"avatarAuthorized":16,"sourceUrl":17,"nameValid":18,"tags":19,"tagNames":20},"d1013e_6d85f6c51ef07d7d","雷柏英","深圳大学",null,"特聘教授、博士生导师","人工智能在医学图像处理的研究（超声图像分析、婴幼儿先心病\u002F淋巴结智能诊断、乳腺\u002F甲状腺超声图像分析）；神经影像分析（阿尔茨海默病、帕金森病、自闭症、强迫症智能诊断）；肿瘤图像的分割和识别（黑色素瘤、胃癌、眼科AI、鼻咽癌大数据分析）","雷柏英，国家级青年人才入选者，深圳大学特聘教授，西安电子科技大学客座教授，博士生导师，获新加坡南洋理工大学博士学位。主要研究方向为医学图像处理和人工智能。在IEEE TPAMI、TNNLS、TMI和MedIA等以第一\u002F通讯作者(含共同)发表SCI论文100余篇(6篇ESI高被引，1篇热点论文)。谷歌学术总引用超11600次，H指数54。主持国家自然科学基金联合基金重点1项、面上2项等项目20余项（含国家级7项）。现任IEEE TNNLS、TCYB、TMI、J-B-HI、Medical Image Analysis等10种SCI期刊编委。","广东省",100,false,"https:\u002F\u002Fmed.szu.edu.cn\u002Fszdw\u002Fjszgml\u002Fswyxgcxy2\u002Fcontent_8350",true,[],[],{"id":22,"name":23,"orgName":24,"school":25,"gender":26,"title":27,"degree":28,"honor":10,"position":10,"researchDirection":29,"intro":30,"province":31,"completeness":15,"avatarAuthorized":16,"sourceUrl":32,"nameValid":18,"tags":33,"tagNames":34},"cd15d0c7-8186-ad2c-bfe1-9fae6d1d11e1","马峻岩","长安大学信息工程学院","长安大学","男","副教授","博士","1、自动驾驶系统仿真、测试与验证\n2、FPGA加速的物联网固件模糊测试方法\n3、智能网联环境下新型混合交通流管控\n2027年拟招收博士研究生1名（留学生），研究生2-3名，要求通过CET-6考试，拥有对技术与学习的热情。课题组科研环境良好，氛围融洽，注重学生理论与实践能力的培养，诚挚欢迎你的加入！学硕招生代码：计算机科学与技术（081200）、软件工程(083500)专硕招生代码：电子信息（085400），计算机、软工方向特别联系方式：WVd4bGVHMWhhbmxBY1hFdVkyOXQ=，b4$e64 10 encoding（请附个人简历）调剂考生注意：本校调剂要求具有一定门槛（本科、报考均为“双一流”；只接受学硕调剂；外语+数学成绩不低于180分）请通过长安大学研招办确认自己符合调剂要求后，再与本人联系调剂事宜。毕业生研究方向及就业去向MUHAMMAD UMER ABBASI，基于LLM的事故场景重构，长安大学博士研究生王品，基于LLM的自动驾驶测试，汇丰科技中国陈文君，深度学习与知识图谱，吉利汽车张伟杰，智能网联环境协同管控建模，金风科技股份有限公司冯中文，嵌入式系统模糊测试，事业单位公务员李博轩，自动驾驶测试，深圳魔耳乐器刘晨颖，智能网联交通流协同控制，陕汽集团胡飞飞，微控制器固件模糊测试，陕汽集团赵紫轩，自动驾驶多模式混合交通流，应用材料（Applied Materials China）窦依依，智能网联交通流协同控制，河南中天高新智能科技股份有限公司史静，知识图谱与智能车测试，中国建设银行王卓，自动驾驶测试，比亚迪周婉金，嵌入式软件运行时验证，上海合见工业软件集团有限公司田叶凡，智能车路系统测试，中国农业发展银行研发中心朱家宝，智能车路系统测试，同花顺研发中心堵白雪，边缘计算与交通安全，中国农业发展银行研发中心MOUSSA SALI，智能车路系统测试，长安大学博士研究生许良，NLP与智能车测试，西安中兴通讯李尚荣，物联网软件测试，西安兆芯集成电路有限公司张佳雨，机器学习与智能车测试，杭州有赞科技有限公司刘仟金，机器学习与交通安全，浦发银行研发中心李剑龙，三维场景语义分割，紫光展锐李易，物联网软件测试，西安兆芯集成电路有限公司张颖，机器学习与智能车测试，中国移动通信集团陕西有限公司张 特，物联网软件故障检测，百度王 瑾，物联网软件故障检测，浙江宇视科技有限公司","马峻岩，男，博士，副教授，硕士生导师，国际生博士生导师，计算机科学与技术系副主任。主要从事嵌入式系统与软件、智能车路系统方面的研究。主持\u002F参与国家自然科学基金、国家重点研发计划、交通部信息化重大专项、国家科技支撑计划等课题的研究工作。相关成果在《计算机学报》、《中国公路学报》、《Automated Software Engineering》、LCTES、IPSN、SenSys、ICSE、ISSRE等重要学术期刊或国际学术会议上发表。受邀担任《IEEE Transaction on Computers》、《IEEE Transaction on Intelligent Transportation Systems》、《Neurocomputing》、《计算机学报》、《中国公路学报》、IEEE GLOBECOM、KIPS CUTE、IEEE ITSC、IEEE ISC2、IEEE RCAR等期刊及国际会议等的审稿专家。获得陕西省科学技术奖一等奖1项，发表学术论文40余篇，取得发明专利19项、实用新型专利10项。 \n                                \n                                \n                                    \n                                         社会职务 \n                                    \n                                     中国计算机学会（CCF）嵌入式系统专业委员会执行委员\n中国计算机学会（CCF）软件工程专业委员会委员\n陕西省宇航学会科普专委会委员\n中国计算机学会（CCF）会员\nAssociation for Computing Machinery（ACM）学会会员","陕西","http:\u002F\u002Fjs.chd.edu.cn\u002Fxxgcxy\u002Fmjy\u002Flist.htm",[],[],{"id":36,"name":37,"orgName":38,"school":25,"gender":26,"title":39,"degree":28,"honor":10,"position":10,"researchDirection":40,"intro":41,"province":31,"completeness":15,"avatarAuthorized":16,"sourceUrl":42,"nameValid":18,"tags":43,"tagNames":44},"6ad61771-e8c7-da20-9c87-c231b4e3835a","丁明涛","长安大学地质工程与测绘学院","教授","理论：人工智能、多模态大模型、模式识别方法：遥感\u002F无人机影像语义分割、分类、配准、变化检测、融合应用：灾害遥感、生态遥感","丁明涛，男，湖北天门人。2004、2007、2010年获西北工业大学理学学士、硕士、博士学位，2010.12-2012.12年于美国杜克大学从事博士后研究工作，2013年获香港中文大学邀请从事研究助理工作半年。2013.07入职长安大学，现任长安大学地测学院测绘系教授、博士生导师。主讲课程《微波遥感原理》、《摄影测量原理与应用》、《数据结构》、《数据库原理》。 \n                                \n                                \n                                    \n                                         社会职务","http:\u002F\u002Fjs.chd.edu.cn\u002Fdzgcychxy\u002Fdmt\u002Flist.htm",[],[],{"id":46,"name":47,"orgName":38,"school":25,"gender":26,"title":39,"degree":48,"honor":10,"position":10,"researchDirection":49,"intro":50,"province":31,"completeness":15,"avatarAuthorized":16,"sourceUrl":51,"nameValid":18,"tags":52,"tagNames":53},"7024058c-a3ec-ade3-fda3-207ad56b21e8","王万银","工学博士","研究领域：重、磁方法理论及应用研究       （1）重磁位场数据处理、转换理论及应用研究。重磁位场数据处理和转换主要有位场延拓、导数换算、方向和分量转换以及位场分离等。在曲面位场处理和转换方面从1987年开始，先后提出了三角函数法的理论和有关方法技术、波数域（频率域）单层位和偶层位法的有关方法技术、整体布置等效源分块反演等效源的关键技术；完善了已有的空间域偶层位法、泰勒级数“曲化平”方法。提高了曲面位场数据处理和转换的效率、精度及适应性。从2006年开始，将最小曲率方法应用于位场数据处理中，解决了位场数据扩边、网格化以及位场分离和噪声压制问题。从1990年开始，在位场延拓、磁异常分量及磁化方向转换方面，利用自适应滤波进行位场向下延拓和中低纬度地区变磁异常分量方向和变磁化方向化极处理，解决了不稳定性问题。这些方法技术均取得了很好的应用效果。       （2）重磁正、反演方法理论及应用研究。重、磁正演是反演的基础，反演主要包括地质体特征位置反演、界面起伏或几何参数反演以及物性反演三个方面。从1999年开始，在地质体特征位置反演方面，提出了归一化总水平导数垂向导数（NVDR－THDR）位场边缘识别方法，以及正则化技术和归一化垂向导数技术，解决了比值类和极大值类位场边缘识别方法的准确性和稳定性问题；研究了位场边缘识别中垂向导数零值位置、总水平导数极值位置和解析信号振幅极值位置的空间变化规律；研究了基于曲率属性、局部波数、解析信号振幅、欧拉反褶积、沃纳反褶积等的位场边缘参数自动反演技术，研究了消除多解性的关键技术。从1990年开始，在重、磁物性界面起伏反演方面，研究了波数域（频率域）物性界面正演快速收敛和反演稳定收敛的关键技术，解决了频率域物性界面正演效率低、反演不能稳定收敛的问题；研究了空间域间断界面起伏的反演方法，提出了基于Lp范数的空间域间断界面目标函数建立方法和NVDR-THDR裂陷边界识别方法，解决了裂陷盆地基底起伏反演难题。从1995年开始，在物性反演方面，提出了以相关系数为目标函数、相关搜索黄金分割法为最优化方法的物性反演算法，解决了物性反演受位场背景场影响的问题，显著提高了反演效果；提出了以NVDR-THDR和NVDR-ASA（归一化解析信号振幅垂向导数）优选靶区的关键技术，从而提高了物性反演的效率和精度；研究了不同范数目标函数对物性反演效果的影响问题，解决了范数选择问题；研究了重磁位场垂向识别能力和横向分辨能力，并将此研究成果用于物性反演，解决了深度加权问题。这些方法均取得了很好的应用效果。       （3）“深地”探测研究。“深地”探测研究始于1986年，在新疆“305”项目、深部探测项目、国家重点研发计划“深地资源勘查开采”等项目的资助下，利用重磁资料，并结合其他地球物理资料和地质资料开展矿产资源分布和深部构造研究。利用航磁资料研究了全国陆域深部构造分布特征；利用重、磁资料先后在新疆、甘肃、陕西、江西、山东等地研究了岩体分布位置、古（破）火山口的分布位置、矽卡岩分布位置，达到寻找铜镍矿体、磁铁矿体等金属矿体的目的。       （4）“深海”探测研究。“深海”探测研究始于1999年，在国家科技重大专项子课题和国土资源部全国油气资源战略选区调查与评价国家专项的资助下，在中国海洋石油总公司研究中心的大力支持下，先后在我国近海盆地（南海盆地、东海盆地、黄海盆地、渤海盆地）完成了断裂分布、第三系厚度、中生界厚度、古生界厚度、火成岩分布、莫霍面和居里面起伏、岩石圈厚度等特征的研究工作，并探讨了深大断裂、火成岩以及圈层构造（岩石圈、地壳、磁性层等）与含油气盆地的关系问题，这些研究成果在我国近海盆地的形成和演化、油气资源勘探等方面发挥了重要作用。近年来在国家科技重大专项子课题和中石油杭州地质研究院的资助下，在墨西哥湾地区、南大西洋两岸和东非海岸地区完成了断裂分布、盆地分布、火成岩分布、深部构造分布特征以及CO2分布等的研究工作，该研究成果为我国在海外油气资源勘探提供了重要支撑","王万银，男，汉族，1962年06月生，甘肃省庆阳市镇原县人。1979－1983年在长安大学（西安地质学院）攻读“地球物理勘探”专业获工学学士学位，毕业后留校任教。1987－1990年在长安大学（西安地质学院）攻读“应用地球物理”专业获工学硕士学位，导师为重磁勘探专家潘作枢教授；2003－2009年在长安大学攻读“地质工程（应用地球物理方向）”专业获工学博士学位，导师为地震勘探专家朱光明教授。1991年晋升为讲师，1997年破格晋升为副教授，2010年晋升为教授，2019年晋升为三级教授。2002年遴选为长安大学硕士生导师，2012年遴选为长安大学博士生导师。2022年06月在长安大学退休。       自1983年留校任教以来，承担的本科生课程主要有：计算机应用基础、Fortran语言程序设计、软件工程概论、算法分析引论、普通物探、重力勘探、磁力勘探、重磁法勘探、重磁勘探专题、重磁资料处理和解释、地球物理概论、数值计算方法等。承担的研究生课程主要有：最优化方法、重磁场数值模拟、位场反演理论等。2000年开始招收第一届硕士研究生，培养硕士生66人；2011开始招收第一届博士研究生，培养博士研究生20人（已毕业15人，在读5人）。硕士研究生和博士研究生均招收地球物理学（固体地球物理学和空间物理学方向）、地质资源与地质工程（地球探测与信息技术方向）两个专业。       科学研究中从事重磁方法理论及应用研究。主要从事重磁位场数据处理、转换理论及应用研究，重磁正、反演方法理论及应用研究，“深地”探测研究和“深海”探测研究。已发表科研论文128篇（其中SCI收录53篇），著作3部（独著1部、合著2部）。 \n                                \n                                \n                                    \n                                         社会职务 \n                                    \n                                     （1）2013—2017和2018—2022教育部高等学校地球物理学类专业教学指导委员会 委员。（2）2020－2024年陕西省高等学校教学指导委员会数理类工作委员会 副主任委员。（3）第五、六、七、八、九届中国地质学会勘探地球物理专业委员会委员（2001—2024）。（4）第四、五届中国地球物理学会海洋地球物理专业委员会委员（2015—）。（5）第一届中国地球物理学会航空航天地球物理专业委员会副主任委员（2021—）。（6）中国地震学会地壳深部探测专业委员会 委员（2023—）。（7）第一届海洋油气勘探国家工程研究中心技术委员会委员、重磁数据分析分中心主任（2021—2025）","http:\u002F\u002Fjs.chd.edu.cn\u002Fdzgcychxy\u002Fwwy100\u002Flist.htm",[],[],{"id":55,"name":56,"orgName":24,"school":25,"gender":57,"title":27,"degree":28,"honor":10,"position":10,"researchDirection":58,"intro":59,"province":31,"completeness":60,"avatarAuthorized":16,"sourceUrl":61,"nameValid":18,"tags":62,"tagNames":63},"d3adaa29-d89c-57f7-87a3-0b7fec18933b","宋蓓蓓","女","研究领域为围绕小样本、小目标、小网络的模式识别与智能系统（人工智能、深度学习）：1）遥感影像智能分析：场景分类、目标检测、场景分割2）视频图像智能处理：目标检测与跟踪3）零样本\u002F小样本学习4）图像压缩：新型图像变换、信源编码，AI图像压缩5）图像复原：去噪、增强、超分辨、光谱重建6）人工智能，深度学习图像处理算法的边缘端部署应用硬件条件：1）配置Nviida GTX1070-8GB、GTX1080TI-11GB(3584 Cuda核)、RTX2080TI-11GB(4352 Cuda核)、RTX3090-24GB(10496 Cuda核)、RTX4090-24GB(16384 Cuda核)、RTX5090D-32GB(21760 Cuda核) GPU电脑\u002F小型工作站多台，满足不同规模深度学习训练需求2）用于深度学习部署的全系列 Nvidia 嵌入式GPU：Jetson Nano(128核)、Jetson Tx2(256核)、Jetson Xavier Nx(384核)、Jetson Xavier(512核)、Jetson Xavier Orin（2048核）3）用于通信信号处理的SDR(软件无线电平台)：ADALM-PLUTO、USRP N210、USRP B2104）FPGA开发板：ZedBoard(Xilinx Zynq UltraScale XC7Z020-CLG484-1)、Ultra96（Xilinx Zynq UltraScale+ MPSoC ZU3EG A484）、ZCU106（Zynq UltraScale+ MPSOC XCZU7EV-2FFVC1156）可部署深度学习研究生招生情况：2016级：王珍2017级：孔方方2018级：赵军2019级：何帆、马穗娜2020级：董杨洋、邱地发2021级：于淑芳、刘锦辉、毕梦昭2022级：原洁冉、刘有继2023级：杜文旺、王哲、高攀、毛楠2024级：陈云飞、杜浴阳2025级：保秋蝶、王晓晗2026级：韩蕊、黄宇晨2027年招生计划计划招生学术硕士1~2名（具有良好的C\u002FPython语言编程基础和数学基础，硕士阶段将主要以基于AI的算法研究为培养方向，意愿做软硬件结合的系统研究更佳，有大学生数学建模竞赛、计算机\u002F程序\u002F软件设计竞赛获奖经历优先），专业硕士1~2名（具有良好的C\u002FC++语言编程基础，了解嵌入式硬件系统，硕士阶段将主要以嵌入式软件设计\u002FC、C++、Python, FPGA设计\u002FVHDL、Verilog, 高性能计算（超高速、高带宽网络数据传输、存储与处理）为培养方向，有大学生电子设计竞赛、计算机\u002F程序\u002F软件设计竞赛获奖经历优先）","2008年毕业于西安电子科技大学获得博士学位，2013年被评为长安大学副教授，2016年被聘为硕士研究生导师。研究方向主要为交通视频图像处理、卫星遥感影像方面的理解与分析，以及深度学习处理与人工智能应用。具体包括图像压缩、图像重建、图像分类、图像分割、目标检测与识别、运动目标跟踪、通信信号识别、嵌入式GPU实时智能处理系统。近年主持陕西省自然科学基金项目一项、中央高校基本科研基金项目2项、横向项目一项，参与国家自然科学基金项目2项，发表论文十余篇，参与编写专著1部。 \n                                \n                                \n                                    \n                                         社会职务",96,"http:\u002F\u002Fjs.chd.edu.cn\u002Fxxgcxy\u002Fsbb\u002Flist.htm",[],[],{"id":65,"name":66,"orgName":67,"school":25,"gender":57,"title":68,"degree":48,"honor":10,"position":10,"researchDirection":69,"intro":70,"province":31,"completeness":60,"avatarAuthorized":16,"sourceUrl":71,"nameValid":18,"tags":72,"tagNames":73},"76dd2bdf-0595-26bc-09dc-655ec9a5a846","师艳子","长安大学汽车学院","讲师","多模态信息智能处理（检测、分割、跟踪等）及其在自动驾驶、智慧交通领域的应用硕士研究生招生专业为智能电动车辆、交通运输工程、交通运输。如果你有兴趣报考我的研究生，请将下列材料打包发送至我的邮箱：个人简历、成绩单、以及竞赛等支撑材料！","师艳子，长安大学，汽车学院，讲师，硕导。2022年06月获西安电子科技大学工学博士学位，2022年09月至今在长安大学任教。研究方向为图像智能处理及其在自动驾驶、城市遥感中的应用。相关成果发表在IEEE TIP、IEEE TGRS、IEEE GRSL等期刊上，其中2篇为ESI高被引论文。主持陕西省博士后科研项目一等资助、中国博士后科学基金面上资助、中央高校基金、横向科研项目等。 \n                                \n                                \n                                    \n                                         社会职务 \n                                    \n                                     1、IEEE 会员，中国图象图形学学会会员。2、中国图象图形学学会图像应用与系统集成专业委员会委员、遥感图像专业委员会委员3、遥感领域国际期刊Remote Sensing（中科院二区）特刊“Advances in Scene Understanding with Hyperspectral Remote Sensing: From Data Benchmarks to Applications”客座编辑4、《IEEE Transactions on Neural Networks and Learning Systems》《IEEE Transactions on Geoscience and Remote Sensing》《IEEE Transactions on Image Processing》《Geo-spatial Information Science》等国际权威期刊审稿人5、国际会议2021 International Geoscience and Remote Sensing Symposium目标检测分会场主席","http:\u002F\u002Fjs.chd.edu.cn\u002Fqcxy\u002Fsyz\u002Flist.htm",[],[],{"id":75,"name":76,"orgName":77,"school":25,"gender":26,"title":27,"degree":28,"honor":10,"position":10,"researchDirection":78,"intro":79,"province":31,"completeness":60,"avatarAuthorized":16,"sourceUrl":80,"nameValid":18,"tags":81,"tagNames":82},"5aeb9950-17e7-6c10-0f0a-4ae2f575afa6","徐小波","长安大学电子与控制工程学院","研究方向为深度学习：1、图像类：(1)、对抗生成网络、扩散模型，应用场景为单样本\u002F少样本情况下图像生成与识别。(2)、语义分割\u002F模式识别，应用场景为小样本情况下缺陷识别。2、时间序列类：Transformer网络，应用场景为基于大样本、基于注意力机制的表格数据预测。3、图类：图神经网络研究项目主要为交通、光伏、医学影像、微电子等行业与人工智能的结合","徐小波，男，42，博士，副教授，2009年3月毕业于西安电子科技大学微电子学院，获硕士学位，硕士论文题目《MEMS传感器弱信号检测电路及集成设计》，2012年3月获西安电子科技大学微电子学与固体电子学博士学位，博士论文题目《SOI SiGe HBT性能与结构设计研究》，现在长安大学电子与控制工程学院机器人工程系从事科研和教学。近几年主持国家自然科学基金、博士后科学基金、陕西省自然科学青年基金、陕西省自然科学青年基金等，参与项目多项。在IEEE Transactions on Electrons Devices、Solid State Electronics、Superlattices and Microstructures、Chinese Physics B、Chinese Physics Letters等期刊公开发表第一作者学术论文20余篇，其中14篇SCI收录，6篇EI收录。当前主要研究领域或方向为机器学习：(1) 自然语言处理(NLP)方向，主要为表格预测(tabular prediction)； (2) 生成深度网络：主要为对抗生成网络(GAN)和扩散模型(diffusion model)，生成AI图像或者数据。(3) 目标检测。主要为a. 卷积神经网络如：U网络(U-Net)和可变形卷积网络（deformable ConvNet）             b. vision transformer以及后续模型(4) 图神经网络：主要为注意力机制+图卷积的各种组合应用场景主要为交通、光伏、医学影像、微电子等行业与人工智能的结合。 \n                                \n                                \n                                    \n                                         社会职务 \n                                    \n                                     1、IEEE wireless communications 、solid state electronics、IET electronics letters等期刊审稿人；2、教育部全国硕士博士论文审稿人；3、mdpi SCI期刊客座编辑；","http:\u002F\u002Fjs.chd.edu.cn\u002Fdzykzgcxy\u002Fxxb\u002Flist.htm",[],[],{"id":84,"name":85,"orgName":24,"school":25,"gender":26,"title":27,"degree":28,"honor":10,"position":10,"researchDirection":86,"intro":87,"province":31,"completeness":88,"avatarAuthorized":16,"sourceUrl":89,"nameValid":18,"tags":90,"tagNames":91},"44673b8b-ceef-7708-1b8b-5e795146aa40","马仑","1.利用多源异构感知数据（包括穿戴设备与雷达）结合深度学习\u002F机器学习的人类行为识别（主要致力于障碍人群伤害行为的智能识别）2.多模态遥感图像语义分割3.多通道合成孔径雷达（SAR）成像及系统误差估计与补偿4.并行交替采样技术在超宽带信号采样中的应用","社会职务 \n                                    \n                                     IEEE期刊审稿人",91,"http:\u002F\u002Fjs.chd.edu.cn\u002Fxxgcxy\u002Fml101\u002Flist.htm",[],[],{"id":93,"name":94,"orgName":95,"school":25,"gender":26,"title":68,"degree":48,"honor":10,"position":10,"researchDirection":96,"intro":97,"province":31,"completeness":88,"avatarAuthorized":16,"sourceUrl":98,"nameValid":18,"tags":99,"tagNames":100},"7694407a-a422-3ab5-b16b-a0e05863f78a","左琛","长安大学运输工程学院","1. 基于视觉基础模型的公路交通设施无人机巡检与智能图像识别方法研究伴随着飞控能力和计算平台的发展，无人机已经成为进行公路交通基础设施巡检的新兴工具。然而，无人机图像中扰动因素多、场景变化大，给后继的图像分析与智能识别方法带来巨大挑战。本课题组针对路面病害、标线标识、沿线设施、道路边坡等多种细分养护场景，以海量无人机航拍图像为数据基础，运用视觉基础模型、图像分割大模型、多模态数据处理等人工智能和计算机视觉前沿技术，探索各类异常结构的视觉响应特征，求解行业规范文本和巡检图像之间的相互对应关系，建立兼具计算效率和识别精度的智能图像分析方法，显著提高深度神经网络的训练速度、标注效率和泛化能力，为公路交通基础设施的状态检测和性能评估提供重要依据。1.1 基于基础模型的路面病害识别与搜索方法及时准确地发现裂缝、坑槽、修补等路面病害，是公路预防性养护和智慧化养护的重要内容。近年来，以卷积神经网络为核心的深度学习技术已经成为了分析巡检图像的主流方法。然而，当前技术多基于有监督学习框架，难以有效应对道路病害多样的形态特征，识别方法的泛化能力有限。本课题组基于无人机高分辨率图像，以视觉基础模型为核心技术手段，探索各类路面异常样例的高阶视觉特征，建立高性能路面病害识别方法。具体内容包括：(1)使用DINOv2、Web-SSL等视觉基础模型，充分利用自监督学习、Vision Transformer和海量无标注数据集，提取图像视觉特征；(2)运用距离度量、流形学习和无监督聚类技术，发现道路路面区域，移除不相关图像块；(3)使用XGBoost、TabPFN等有监督分类器，建立主动学习框架，促使计算机理解视觉特征与病害样本之间的对应关系，预测病害的发生位置、损坏类型和损坏程度；(4)基于典型病害样例库，运行近似近邻搜索方法，求解路面病害的类内多样性和场景变化性，实现异常结构的精细搜索与快速排查，探索道路病害的时空变化规律。1.2 图像分割大模型支持的交通标线缺损定位方法保障交通标线的可见性和清晰度，是道路设施养护的重要环节。基于深度神经网络的目标检测和语义分割方法是目前进行破损标线识别的主流技术手段。然而，神经网络的性能高度依赖人工标注的质量和规模，如何有效建立高质量数据集，提高神经网络的训练效率，减少人工标注工作量，成为了重要且紧迫的科研话题。本课题组引入图像分割大模型技术，依据标线颜色等先验信息，引导图像大模型理解交通设施养护场景，建立交通标线缺损快速检测和准确评估的技术方法。具体内容包括：(1)基于图像分割大模型SAM,启动全局分析模式，自动划分无人机巡检图像，依据颜色信息确定道路路面区域，划定研究范围；(2)使用DINOv2基础模型，运用Hausdorff距离和余弦距离，量化无人机图像序列的相似性，获得代表性图像样例；(3)基于代表性图像，训练YOLO和DETR目标检查网络，准确定位减速标线、车道线、导向箭头和导流线破损；(4)启动图像分割大模型SAM，分析交通标线样例，预测标线初始状态。基于阈值分割方法，提取标线的现存可见区域。计算标线的缺失区域比例，定量评估标线健康状态。1.3 多模态学习赋能的交通沿线设施快速识别方法交通标志、交安设施、交通监控等沿线设施是交通系统的基本组成，定位和维护沿线设施是进行基础设施养护的基本要素。基于YOLO等目标检测网络，计算机能够实现无人机航拍图像的高效处理。然而，当前的有监督学习方法高度依赖人工标注数据集，能以有效应对光照条件、巡检场景和飞控参数的显著变化，识别方法的泛化能力有限。本课题组引入多模态分析技术，探索交通标志图像和行业规范文本之间的映射关系，在共享特征空间内实现多模态样例的准确对齐和配准，提高交通沿线设施的快速定位和精细分类。具体内容如下：(1)启动Grounding DINO、YOLO-World、YOLOE等开放词汇目标检测程序，合理设定关键字提示词，建立沿线设施样例数据集；(2)运用知识蒸馏技术，建立教师-学生结构，去除任务无关神经元，获得小尺寸高效率目标检测网络；(3)使用视觉基础模型分析无人机图像，使用文本编码器分析行业规范文本，运用线性映射层实现共享特征空间内的样本对齐，实现交通沿线设施的精细化分类。1.4 光学、红外与三维点云联合驱动的道路边坡隐患识别方法快速发现边坡落石、岩体开裂、植被侵入等异常案例，是维护道路边坡安全的重要因素。在无人机智能巡检框架内，如何有效整合光学图像、红外图像、三维点云等多模态数据采集手段，提高边坡异常结构的识别质量，成为了重要的研究话题。本课题组针对山区公路和沿海公路场景，有机结合设备、数据、技术和交通养护部门需求，以海量无人机图像为数据基础，运用深度神经网络、视觉基础模型、多模态数据处理等手段，建立高性能道路边坡智能巡检方法。具体内容如下：(1)启动EfficientNet、Vision Transformer、ConvNeXt、Mamba等多种前沿深度神经网络，探索各类神经网络的性能边界，实现边坡落石和岩体开裂的快速定位和分类；(2)针对水库边坡场景中的少样本学习难题，使用DINOv2视觉基础模型分析RGB、红外和点云图像，编程实现特征级融合和决策级融合框架，实现边坡落石和植被侵入的快速识别；(3)基于海量无标注图像，使用自监督学习和对比学习技术探索光学-红外-点云图像之间的匹配关系，促使计算机自主发掘边坡结构之间的内在关系和发展趋势，实现多模态数据对齐，获得与巡检场景相匹配的高质量图像编码器。2. 基于开放词汇目标检测和视觉基础模型的危化品车辆识别方法从海量交通监控视频中快速发现危化品车辆，是智慧交通系统的关键环节，是提高通行效率、保障交通安全、促进绿色发展的基本前提。近年来，深度学习和计算机视觉技术成为了实现交通感知的主流方法。然而，多样的视频采集设备、繁杂的交通通行场景和稀缺的危化品车辆样例，给深度神经网络的推广应用带来了巨大挑战。为了提高泛化能力并简化训练流程，本课题组将开放词汇目标检测和视觉基础模型引入到交通视频分析领域，充分利用通用视觉特征，建立高性能危化品车辆识别方法。具体内容包括：(1)启动YOLO-World目标检测程序，合理设置关键字提示词，快速提取交通监控视频中的车辆样例。为了消除冗余信息，使用ByteTrack和SAM2技术，完成车辆的轨迹跟踪；(2)使用DINOv2视觉基础模型，提取车辆样例的视觉特征，使用UMAP和谱聚类技术理解车辆样例之间的相似性关系；(3)使用k近邻搜索去除YOLO-World的噪声样例，使用XGBoost分类器预测车辆类型，有效应对夜间、降雨等复杂场景，建立具有高泛化能力和强鲁棒性的危化品车辆识别方法。3. 孔隙结构与物理属性联合约束的非均质数字岩心建模方法3.1 基于通用图像特征的非均质岩心表征方法3.2 基于机器学习技术的三维数字岩心快速建模方法3.3 贝叶斯证据学习驱动的地质模型空间不确定性量化方法4. 基于视觉基础模型的城市更新区域与建成环境识别方法对于具有复杂建成环境的老城区，采用人工智能技术可以提高更新规划的科学性，然而现有的目标识别方法高度依赖人工标注数据集，面临更新实践不足、分析精度受限和训练成本过高的局限。将视觉基础模型引入城市更新领域，探讨视觉基础模型支持的老城区更新规划方法：(1)通过等间隔采样构建图像块数据集，使用视觉基础模型提取高维视觉特征；(2)启动余弦距离、流形学习、高斯混合模型等机器学习技术，实现图像块数据集的智能分组；(3)对图像块进行空间转译，精准识别重点区域；结合多维要素综合评判，优化智能识别结果，指导后续更新规划实践。以陕西省榆林市清涧县老城区为例，探索该技术方法在城市更新规划实践中的应用，以期为老城区的城市更新提供新的思路","左琛，本科毕业于四川大学电子信息工程专业，博士毕业于西安交通大学信息与通信工程专业，美国斯坦福大学访问学者。现任长安大学运输工程学院讲师，数据与系统工程系副主任，数据与系统工程党支部宣传委员。申请人长期从事机器学习与计算机视觉相关研究工作，目前主持国家自然科学基金青年科学基金项目1项、陕西省自然科学基础研究计划一般项目(青年)1项、陕西省交通运输厅交通运输科研项目1项、山东省交通运输厅先行试验项目1项、中央高校基本科研业务费专项资金资助项目2项。作为技术负责人，参与国家自然科学基金面上项目2项、陕西省科学技术厅重点研发计划项目1项、陕西省交通运输厅重点项目2项、河北省交通厅科技项目1项。以第一作者和通信作者身份，累计发表学术论文10余篇，包括《IEEE Transaction on Geoscience and Remote Sensing》《Water Resources Research》《Remote Sensing》等，参加国内外高水平学术会议并做专题报告6次，已授权发明专利2项。 \n                                \n                                \n                                    \n                                         社会职务","http:\u002F\u002Fjs.chd.edu.cn\u002Fysgcxy\u002Fzc5\u002Flist.htm",[],[],{"id":102,"name":103,"orgName":104,"school":25,"gender":26,"title":68,"degree":48,"honor":10,"position":10,"researchDirection":105,"intro":106,"province":31,"completeness":107,"avatarAuthorized":16,"sourceUrl":108,"nameValid":18,"tags":109,"tagNames":110},"bb90d0fc-4abe-f2a5-c097-f137d27e6188","张弛","长安大学工程机械学院","主要研究领域包括：1、智能材料及其应用。主要研究基于电致变形材料（包括但不限于介电弹性体-DEA、聚氯乙烯凝胶驱动器-PVCG）的新型驱动器设计，重点为柔性光学和航空航天领域。2、基于深度学习和图像处理的工业和工程检测技术。依托于企业需求，利用深度学习和机器视觉，实现工业工程自动化检测，例如路面、桥面、建筑物、发动机缸体等瑕疵病害检测。3、非标自动化设计。依托于企业需求，提供非标设备的设计和方案。部分成果展示☆智能材料及其应用智能窗户\u002F智能显示    smart window\u002Fsmart displayYour user agent does not support the HTML5 Video element.具有大变焦范围的液体透镜  Tunbale lens with large focal length tuning range            Your user agent does not support the HTML5 Video element.快响应、长寿命弹性透镜变焦效果展示         HASEL阵列                   环形EHD驱动器☆基于深度学习的检测技术                  水泥混凝土目标检测                   水泥混凝土目标分割☆非标设计及上位机开发      复合分选设备             高速带斗式提升机                     SPC智能检测站科研平台智能材料研发平台（200平）联合西安交大，西安工程大学，依托艾博电子与艾博材料公司，具有材料实验室200平，电子车间400平及办公约400平，主要研究材料先进制备及性能优化，新型驱动器设计开发，具有材料制备、表征、测试、控制等相关仪器设备与平台。实验室主页链接：http:\u002F\u002Fwww.ablesmat.com\u002F合作姓名单位职务专业朱子才①西安交通大学副教授PVCG及其驱动器研究刘学婧西安工程大学副教授DEA理论与器件设计魏晓东伶机驱动技术研究院人工智能工程师机器视觉\u002F深度学习①http:\u002F\u002Fgr.xjtu.edu.cn\u002Fweb\u002Fzicaizhu\u002Fhome?p_p_id=com_liferay_login_web_portlet_LoginPortlet&p_p_lifecycle=0&p_p_state=normal&p_p_state_rcv=1备注：每年可招收4名硕士研究生(学术型\u002F专业型均可），欢迎机械、电子、力学、高分子材料、计算机等专业同学报考","张弛，男，工学博士，讲师，硕士生导师，山东菏泽人。2012年毕业于四川大学制造科学与工程学院机械设计制造及其自动化专业，获工学学士学位。2012年至2018年，硕博连读于西安交通大学机械工程学院，师从陈花玲教授，获工学博士学位。其间于2016年10月至2017年10月博士联合培养于洛桑联邦理工学院，师从智能材料领域专家Herbert Shea教授。2018年9月入职长安大学工程机械学院机械电子工程系。自博士其间一直从事电致变形材料的本构理论及应用研究，在ACS Applied Polymer Materials, Smart materials and structures, Journal of applied physics, Journal of physics D等期刊发表学术论文10余篇，主持和参与横纵向课题10余项。目前主要致力于PVCG和HASEL驱动器在柔性光学和航空航天领域的应用研究。2022年8月进入宁夏巨能机器人有限公司博士后工作站，承担上位机开发、基于深度学习的工业检测技术方向研究。2025年3月进入浙江三星机电股份有限公司，从事EBS电机轻量化研究。自我评价：80后的尾巴90后的头生人，喜欢听70后80后的歌，玩00后10后的游戏。喜欢COD、CF、CSGO等FPS游戏，喜欢Faze Clan，Zywoo，S1mple。喜欢足球，将近20年的拜仁老球迷。喜欢探究新鲜的事物，对科研始终保持着足够的兴趣。每日状态：快乐生活，快乐工作，快乐科研。近况汇报：2025年9月6日，基于PVCg的智能玻璃研究收录于《ACS Applied Polymer Materials》（中科院2区，IF4.7）2025年6月，关于PVCg的中文综述收录于《功能高分子学报》（CSCD收录） \n                                \n                                \n                                    \n                                         社会职务",86,"http:\u002F\u002Fjs.chd.edu.cn\u002Fgcjxxy\u002Fzc102\u002Flist.htm",[],[],{"id":112,"name":113,"orgName":114,"school":25,"gender":57,"title":68,"degree":115,"honor":10,"position":10,"researchDirection":116,"intro":117,"province":31,"completeness":118,"avatarAuthorized":16,"sourceUrl":119,"nameValid":18,"tags":120,"tagNames":124},"3a34a8f2-d6da-1e70-1868-7e677ba71449","王海莉","长安大学理学院","硕士","主要研究方向为：利用PDE及变分法研究图像分割问题","王海莉，1979年3月生，陕西省西安市人。2005年毕业于西北大学数学系，获计算数学硕士学位。现为长安大学理学院数信系教师，讲师。 \n                                \n                                \n                                    \n                                         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