王儒敬：中(zhong)國科(ke)學(xue)院(yuan)合肥物(wu)質(zhi)188bet金宝搏在线院(yuan)合肥智能(neng)機械(xie)研究所總工程師(shi)（原所(suo)長），二級研究員，中科合(he)肥智慧農業谷有限責(ze)任(ren)公司(si)總經理，188bet足球教(jiao)授、博士生(sheng)導(dao)師；兼任國(guo)家自動(dong)化協(xie)會智慧農業專業委(wei)員會主任，農業(ye)傳感器與智能感知(zhi)安徽省技術創新中心主任，安徽省仿生感知與(yu)先進(jin)機(ji)器人技術重點實驗室主任，安徽省(sheng)安徽省(sheng)智慧農業工程實驗室(shi)主任(ren)，模式識(shi)別(bie)與人工智能雜志副(fu)主編；國家科技(ji)部十三五、十(shi)四五(wu)重點專項領域專家，安徽(hui)省數字農業(ye)產業(ye)體系(xi)首席(xi)專家；國(guo)內外核心期刊發(fa)表學術論文200多篇，學(xue)術專(zhuan)著(zhu)1部，獲得國(guo)家(jia)發明(ming)專(zhuan)利(li)100余(yu)項；獲得國家科技進(jin)步二等獎1項(xiang)，安徽省科技(ji)進步一等(deng)獎2項，享譽國(guo)務院津貼。

研究方向：智慧農業，20多(duo)年從事農業人工智(zhi)能的理論方(fang)法研究與智能裝備開(kai)發(fa)。主(zhu)持國家863課題、國(guo)家科技(ji)支撐、國家重點專項、世行農(nong)業科(ke)技基金、國家(jia)自然基金、中科(ke)院STS重點(dian)專(zhuan)項、安徽省重大(da)科(ke)技攻關項目等(deng)科(ke)研課題60余項。突破：高通(tong)量、低(di)成本、智能化(hua)土壤速測(ce)技術，研制成(cheng)功(gong)首(shou)臺套(tao)土(tu)壤(rang)高通量智能檢測機器人，實現復雜(za)土壤成分檢測(ce)智能化，已(yi)由(you)比亞迪代(dai)工量產；突(tu)破復雜自然條件下病蟲草害智(zhi)能識別(bie)技術，獲(huo)國(guo)際(ji)人工智(zhi)能挑戰(zhan)賽冠軍，研(yan)制成功作(zuo)物四情（苗情(qing)(qing)(qing)、墑(di)情(qing)(qing)(qing)、災情(qing)(qing)(qing)、病蟲情(qing)(qing)(qing)）探(tan)測(ce)智能裝備(bei)，農業部發文(wen)全國(guo)推廣，廣泛用于(yu)我國(guo)各種測報裝置(zhi)。

發表文章：

1. Rujing Wang, Rui Li*, Tiaojiao Chen, Jie Zhang*, Chenjun Xie,Kun Qiu,Peng Chen, Jianming Du, Hongbo Chen, Fanglong Shao,Haiying Hu, Haiyun Liu.An automatic system for pest recognition and forecasting, Pest Management Science, 2021,DOI 10.1002/ps.6684

2. Shifeng Dong , Rujing Wang* Jianming Du and Lin Jiao. Enhancement-fusion feature pyramid networkfor object detection, Journal of Electronic Imaging, 2023,32(1):013045-013059

3. Xiaobo Hu, Rujing Wang*, Jianming Du , Yimin Hu ,Lin Jiaoand Taosheng Xu*. Class-attention-based lesionproposal convolutional neuralnetwork for strawberrydiseases identifification , Frontiers in Plant Science, 2023, 10.3389/fpls.2023.1091600

4. Qiong Zhou , Ziliang Huang, Shijian Zheng, Lin Jiao*,Liusan Wang* and Rujing Wang*. A wheat spike detection method based on Transformer, Frontiers in Plant Science,2023,10.3389/fpls.2022.1023924

5. Tianjiao Chen, Rujing Wang*, Jianming Du*, Hongbo Chen, Jie Zhang, Wei Dong,Meng Zhang. CMRD-Net: A Deep Learning-BasedCnaphalocrocis medinalis DamageSymptom Rotated Detection Frameworkfor In-Field Survey, frontiers in plant science, 2023,14, DOI 10.3389/fpls.2023.1180716

6. Junqing Zhang, Rujing Wang *, Zhou Jin, Hongyan Guo , Yi Liu , Yongjia Chang, Jiangning Chen, Mengya Li and Xiangyu Chen. Development of On-Site Rapid Detection Device for Soil Macronutrients Based on Capillary Electrophoresis and Capacitively Coupled Contactless Conductivity Detection (C4D) Method , chemosensors, 2022, 10, 84.doi.org/10.3390/chemosensors10020084

7. Yue Teng, Rujing Wang*, Jianming Du, Ziliang Huang , Qiong Zhou  and Lin Jiao. TD-Det: A Tiny Size Dense Aphid Detection Network under In-Field Environment ,insects, 2022,13(6):501, doi: 10.3390/insects13060501.

8. Ziliang Huang , Rujing Wang , Ying Cao , Shijian Zheng , Yue Teng , Fenmei Wang , Liusan Wang ? , Jianming Du . Deep learning based soybean seed classification,Computers and Electronics in Agriculture, 2022, 202 ,107393

9. Wang R, Liu L, Xie C, Yang P, Li R. AgriPest: A Large-Scale Domain-Specific Benchmark Dataset for Practical Agricultural Pest Detection in the Wild, Sensors,2021,doi:10.3390/s21051601.

10. Wang X, Zhang Z, Wang X, Bao Q, Wang R*, Duan Z. The Impact of Host  Genotype, Intestinal Sites and Probiotics Supplementation on the Gut Microbiota Composition and Diversity in Sheep. Biology ,2021, 10:769. 

11. Wang X, Zhang  Z, Yin W, Zhang J, Wang R*, Duan Z. Interactions between Cryptosporidium, Enterocytozoon, Giardia and Intestinal Microbiota in Bactrian Camels on Qinghai-Tibet Plateau, China. Applied Sciences 11(8):3595,doi:10.3390/app11083595

12. Zhou Man, Liu Liu, and Rujing Wang*. "ReinforceDet: Object Detection by Integrating Reinforcement Learning with Decoupled Pipeline. ", International Conference on Image Processing (ICIP) 2021.

13. Man Zhou and Rujing Wang*. Control Theory-Inspired Model Design for Single Image De-raining. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS，2021.

14. Wang F, Wang R*, Xie C, Yang P, Liu L. Fusing multi-scale context-aware information representation for automatic in-field pest detection and recognition,Computers and Electronics in Agriculture, 2020,105222.

15. Liu L, Wang R*, Xie C, Yang P, Liu L, Zhang J, Wang F, Sudirman S, Li R. Deep Learning based Automatic Multi-Class Wild Pest Monitoring Approach using Hybrid Global and Local Activated Features,IEEE Transactions on Industrial Informatics, 2020.

16. Zhao Y, Liu L, Xie C, Wang R*, Wang F, Bu Y, Zhang S. An effective automatic system deployed in agricultural Internet of Things using Multi-Context Fusion Network towards crop disease recognition in the wild,Applied Soft Computing, 2020.

17. Li D, Wang R*, Xie C, Liu L, Zhang J, Li R, Wang F, Zhou M. A Recognition Method for Rice Plant Diseases and Pests Video Detection Based on Deep Convolutional Neural Network,Sensors, 2020, 20(3).

18. Liu L, Wang R*, Xie C, Yang P, Wang F, Sudirman S, Liu W. PestNet: An End-to-End Deep Learning Approach for Large-Scale Multi-Class Pest Detection and Classification,IEEE Access, 2019: 45301-45312.

19. Li R, Jia X, Hu M, Zhou M, Li D, Liu W, Wang R*, Zhang J, Xie C, Liu L, Wang F, Chen H, Chen T, Hu H. An Effective Data Augmentation Strategy for CNN-Based Pest Localization and Recognition in the Field,IEEE Access, 2019: 160274-160283.

20. Yushan Zhao, Liu Liu, Chengjun Xie, Rujing Wang*, Fangyuan Wang, Yingqiao Bu, and Shunxiang Zhang. An effective automatic system deployed in agricultural Internet of Things using Multi-Context Fusion Network towards crop disease recognition in the wild. Applied Soft Computing,89 (2020): 106128.

21. Liu L, Wang R*, Xie C, Li R, Teng Y. Learning Region-Guided Scale-Aware Feature Selection for Object Detection,Neural Computing and Applications(4), 1-15.2020.

22. Liu L, Wang R*, Xie C, Yang P, Zhang J, Wang F, Sudirman S, Li R. Deep Learning based Automatic MultiClass Wild Pest Monitoring Approach using Hybrid Global and Local Activated Features.” IEEE Transactions on Industrial Informatics. 2020.

23. Liu Liu, Rujing Wang*, Chengjun Xie, Po Yang, Jie Zhang, Fangyuan Wang,Sud Sudirman, Rui Li. ”Deep Learning based Automatic Multi-Class Wild Pest

24. Monitoring Approach using Hybrid Global and Local Activated Features.” IEEE Transactions on Industrial Informatics.

25. Liu Liu, Rujing Wang*, Chengjun Xie, Po Yang, Fangyuan Wang, Sud Sudirman, and Wancai Liu. ”PestNet: An end-to-end deep learning approach for large-scale multi-class pest detection and classification.” IEEE Access. 7 (2019): 4530145312.

26. Li R, Wang R*, Xie C, Liu L, Zhang J, Wang F, Liu W. A coarse-to-fine network for aphid recognition and detection in the field,Biosystems Engineering, 2019: 39-52.

27. Li R, Wang R*, Zhang J, Xie C, Liu L, Wang F, Jia X, Hu M, Zhou M, Li D, Liu W, Chen H, Chen T, Hu H. An Effective Data Augmentation Strategy for CNN-Based Pest Localization and Recognition in the Field,IEEE Access, 2019: 160274-160283.

28. Shu Yan, Caoyuan Cui, Bingyu Sun, and Rujing Wang*. Markov Boundary discovery based on variant ridge regularized linear models, IEEE ACCESS, 2019. doi: //doi.org/10.1109/ACESS.2019.2924341.

29. Hongyan Guo, Aiwu Zhao, Qinye He, Ping Chen, Yuanyuan Wei, Xiangyu Chen, Haiying Hu, Min Wang, He Huang, Rujing Wang*. Multifunctional Fe3O4@mTiO2@noble metal composite NPs as ultrasensitive SERS substrates for trace detection. Arabian Journal of Chemistry, 2019, doi: 10.1016/j.arabjc.2019.01.007

30. SU Ya-Ru，RJ Wang，P Chen，YY Wei，LI Chuan-Xi，and HU Yi-min. Agricultural Ontology Based Feature Optimization for Agricultural Text Clustering. Journal of Integrative Agriculture,2012.

31. WEI Yuan-yuan, WANG Ru-jing, HU Yi-minand WANG Xue. From Web Resources to Agricultural Ontology: a Method for Semi-automatic Construction. Journal of Integrative Agriculture, 2012, 11(5): 775-783.

32. Y Wang，C Lu，L Wang，L Song，R Wang，Y Ge. Prediction of Soil Organic Matter Content Using VIS/NIR Soil Sensor.Sensors & Transducers, 2014,168(4):113-119.

33. Rujing Wang , Xiaoming Zhang. Particle swarm optimization with opposite particles. MICAI 2005: Advances in Artificial Intelligence, 2005, 3789: 633-640.

34. Yujie Li, Rujing Wang*, Wei Li, Man Zhou, Yan Wu. Cross-grained context guided Chinese entity extraction with graph convolutional network[C]. Proc.SPIE 11584, 2020 International Conference on Image, Video Processing and Artificial Intelligence.2020.

35. Liu L, Wang R*, Xie C, Yang P, Sudirman S, Wang F, Li R. Deep Learning based Automatic Approach using Hybrid Global and Local Activated Features towards Large-scale Multi-class Pest Monitoring[C]//INDIN 2019:vol. 1, pp.  1507-1510.

36. Shu Yan，Xiaobo Hu, Rujing Wang*. Alternative models for the modified form of ridge regularized linear model in discovering Markov boundary [C], The Second International Conference on Physics, Mathematics and Statistics.

37. Yuanmiao Gui*, Rujing Wang, Yuanyuan Wei, Xue Wang. Construction of protein-protein interactions model by deep neural networks. 2018 International Workshop on Bioinformatics, Biochemistry, Biomedical Sciences (BBBS 2018). DOI: //dx.doi.org/10.2991/bbbs-18.2018.47

38. 王儒敬,　檀敬東, 黃河. 一種新(xin)的復雜(za)自適應搜索模(mo)型, 模式識別與人工智, 2009, 22(6), 815-820.

39. 王儒敬,葛運健, 滕明(ming)貴, 張曉明, 基于粗(cu)集的空(kong)間對象分類學習算(suan)法, 188bet足球學報, 2006,36(2):163-169.

40. RJ Wang, XM Zhang, Particle Swarm Optimization with Opposite Particles, Lecture Notes in Artificial Intelligence-,2005,3789:633-640.

41. 王儒敬，滕(teng)明(ming)貴(gui), 一種用于空間對象屬性預測的空間廣義線性回歸模型, 模式識別與人工智能,2005,18(6):798-712.

42. 王儒敬，白(bai)石磊，毛雪岷. 大(da)型知識庫存儲結構的研究, 計算機工程, 2003, 21(2003): 25-27.