授权的发明专利
[1]. 一种基于Mamba的高效光流估计方法和装置,ZL202511512181.0
[2]. 基于毫米波雷达点云特征的行为识别方法和装置,ZL202410400875.4
[3]. 一种基于注意力机制的骨龄智能评估方法,ZL202310553380.0
[4]. 一种基于视觉传感器采集光流特征的精神疾病识别系统,ZL202310571093.2
[5]. 一种基于图像增强的骨龄评估方法,ZL202210787245.8
[6]. 一种基于神经网络的语音情感识别方法,ZL202210216452.8
[7]. 一种基于细粒度分类的骨龄评估方法,ZL202210039032.7
[8]. 一种基于特征融合的语音情感识别方法,ZL202210217251.X
[9]. 一种面向儿童的阶段性身高预测方法,ZL 202110301506.6
[10].一种基于微表情分析的睡眠障碍判别方法和系统,ZL 202110690775.6
[11].一种基于生长激素治疗的儿童阶段身高预测方法,ZL 202011144782.8
[12].一种青少年儿童身高生长曲线的预测方法,ZL 202011127019.4
[13].一种基于位置点匹配的手腕骨兴趣区域修复方法,ZL 202011124718.3
[14].一种基于深度学习的大规模商标检测方法,ZL 2021116106858
[15].一种基于形状信息的腕骨区域分割方法,ZL 201911066354.5
[16].WSN中的一种流水式栅栏调度算法实现方法,ZL 201910174732.5
[17].一种基于多模块融合的室内外场景识别方法,ZL 201911066345.6
[18].一种手腕部参照骨分割方法,ZL 201910574535.2
[19].基于形状信息和卷积神经网络的CHN法兴趣区域提取方法,ZL201910222145.9
[20].一种能耗均衡的WSN层次路由协议实现方法,ZL201910172818.4
[21].二次部署的WSN栅栏强化方法,ZL201610917720.3
[22].一种基于插值的室内指纹定位方法,ZL201610674271.4
[23].一种基于地磁指纹匹配算法的室内定位方法,ZL201610357732.5
[24].面向地下管道的四向行走智能机器人,ZL201610585931.1
[25].一种地下管道机器人有线通讯协议的方法,ZL201610395761.0
[26].基于加速度计的虚拟电子呼啦圈的实现方法,ZL201610326360.X
学术论文
[1]. Ruiji Xu, Junhao Chen, Runzhe Zhang, Guanglin Dai, and Keji Mao. FaceDepth: A Robust Unimodal Depression Detection Framework Using Invariant Facial Landmark Features[J].ACM Transactions on Multimedia Computing, Communications and Applications. 2026. Appl. 22, 1, Article 25 (January 2026), 27 pages. CCF B类(IF:5.2/Q1),通信作者
[2]. Lingkang Y., Xinyi W., Zhuchenghao W., Yan L., Ruiji X., Keji M., Weiyuan Z., Zhitian Z.. MSE-LAM: Multi-scale emotion recognition network based on local attention mask[J]. Neurocomputing, Vol.668,2026,132279.中科院二区(IF:6.5/Q1)
[3]. Ligang Ren, Yan Ling, Tianxiang He, Juntian Du, Ruiji Xu, Hengtan Zhang, Keji Mao. Multidimensional Speech Feature Extraction for Depression Detection using MDCF-Net[C].2025 IEEE International Symposium on Circuits and Systems (ISCAS),London, United Kingdom, 2025, pp. 1-5. CCF C类会议, 通信作者
[4]. Keji Mao,Ruiji Xu.Multi-Scenario Adaptive Intelligent Assessment Methods for Mental Health[M].Zhejiang Gongshang University Press. Hangzhou, 2025(英文专著)
[5]. He, T., Jiang, K., Qian, Z., Wang, W., Chen, X., Mao, K. A Prediction Method for Adult Height of Children Based on ACPSO-SVR[C]. In: Huang, DS., Pan, Y., Chen, W., Li, B. (eds) Advanced Intelligent Computing Technology and Applications. ICIC 2025. Lecture Notes in Computer Science,2025. vol 15866. Springer, Singapore. CCF C类会议, 通信作者
[6]. Lina Wang, Yan Mao, Jinfeng Xu, Jianan Wu, Kunxiu Wu, Keji Mao, Kai Fang.A ROI Extraction Method for Wrist Imaging Applied in Smart Bone-Age Assessment System[J]. IEEE Journal of Biomedical and Health Informatics.2024,28(8):4410-4420.中科院二区TOP(IF:7.7/Q1)通信作者
[7]. Yantao Shao, Tianxiang He, Keji Mao, Kai Fang, Yan Mao and Wei Wang.Optimizing Future Predictions in Children's Health: Implementing OGPA-enhanced Deep Learning for Precise Child Height Forecasting in the Social Media Age[C].Proceedings of the 2024 27th International Conference on Computer Supported Cooperative Work in Design(CSCWD) May 8-10, 2024, Tianjin, China,73-78. CCF C类会议, 通信作者
[8]. Xingda Yao, Lingkang Ying, Tianxiang He, Ligang Ren, Ruiji Xu, Keji Mao.Depression Detection Based on Multilevel Semantic Features[C].33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17–20, 2024, Proceedings, Part VIII,15023:44-55. CCF C类会议, 通信作者
[9]. Chu Chu, Yangbin Lv, Xingda Yao, Hongwei Ye, Chenyue Li, Xin Peng, Zhiwei Gao, Keji Mao. Revealing quality chemicals of Tetrastigma hemsleyanum roots in different geographical origins using untargeted metabolomics and random-forest based spectrum-effect analysis[J]. Food Chemistry.2024,449:139207.中科院一区TOP(IF:8.4/Q1)通信作者
[10].Kai Fang, Jiefan Qiu, Tingting Wang, Kailu Zheng, Liyao Xing, Keji Mao, Kaikai Chi.IDRes: Identity-based Respiration Monitoring System for Digital Twins Enabled Healthcare[J].IEEE Journal on Selected Areas in Communications.2023,41(10):3333-3348.CCF A类期刊,中科院一区TOP(IF:16.4/Q1)通信作者
[11].Keji Mao,Runhui Jin , Lingkang Ying, Xingda Yao , Guanglin Dai, and Kai Fang.SC-YOLO: Provide Application-Level Recognition and Perception Capabilities for Smart City Industrial Cyber-Physical System[J].IEEE Systems Journal,2023,17(4):5118-5129,中科院二区(IF:4.4/Q2)
[12].Keji Mao,Yuxiang Wang, Ligang Ren, Jinhong Zhang, Jiefan Qiu & Guanglin Dai.Multi-branch feature learning based speech emotion recognition using SCAR-NET[J].Connection Science.2023,35(1):2189217, SCI(IF:5.3/Q2)
[13].Kaiyan Chen, Jianan Wu, Yan Mao, Wei Lu, Keji Mao & Wenxiu He.Research on an intelligent evaluation method of bone age based on multi-region combination[J].Systems Science & Control Engineering.2023,11(1):2233545 SCI(IF:4.1/Q3),通信作者
[14].Mao, K.J., Jin, R.H., Chen, K.Y., Mao, J.F., Dai, G.L. Trinity-Yolo: High-precision logo detection in the real world[J]. IET Image Processing.2023,17(7):2272-2283. CCF C类期刊, SCI(IF:2.3/Q3)
[15].毛科技,武坤秀,陆伟,陈立建,毛家发.优化参考图谱发育指征的CHN智能骨龄评估方法研究[J]. 电子与信息学报, 2023, 45(3): 958-967. EI
[16].Mao K, Xu J, Yao X, Qiu J, Chi K, Dai G. A Text Classification Model via Multi-Level Semantic Features[J]. Symmetry. 2022; 14(9):1938. SCI(IF:2.9/Q2)
[17].K. Fang, W. Lu, X. Zhou, J. Xu and K. Mao. A Multitarget Interested Region Extraction Method for Wrist X-Ray Images Based on Optimized AlexNet and Two-Class Combined Model[J]. IEEE Transactions on Computational Social Systems, 2022,9(6):1624-1634.SCI (IF 4.7/Q1) 通信作者
[18].Kaiyan Chen ,Weiyuan Shi,Keji Mao,et al.Design of Growth Trend Map of Children and AdolescentsBased on Bone Age[J].Computational Intelligence and Neuroscience,vol. 2022, Article ID 1325061, 13 pages, 2022. SCI(IF:3.6/Q2)通信作者
[19].Lijian Chen ,Xinben Fan,Keji Mao,et al.Study of Multidimensional and High-Precision Height Model of Youth Based on Multilayer Perceptron[J].Computational Intelligence and Neuroscience,vol. 2022, Article ID 7843455, 11 pages, 2022. SCI(IF:3.6/Q2)通信作者
[20].Keji Mao,Wei Lu, Kunxiu Wu,et al.Bone age assessment method based on fine-grained image classification using multiple regions of interest[J].Systems Science & Control Engineering,2022,10(1):15-23.SCI(IF:4.1/Q3)
[21].毛科技,汪敏豪,陈立建,等.结合目标检测与匹配修正的手腕骨兴趣区域提取[J].中国图象图形学报,2022,27(3):973-987.
[22].Keji Mao,JinyuXu,RunhuiJin,et al.A fast calibration algorithm for Non-Dispersive Infrared single channel carbon dioxide sensor based on deep learning[J].Computer Communications,2021,179:175-182.SCI,CCF C类期刊(IF:5.0/Q1)
[23].Keji Mao,Lijian Chen,Minhao Wang,et al.Classification of hand-wrist maturity level based on similarity matching[J].IET image processing,2021,15(2):2866-2879.CCF C类期刊,SCI(IF:2.3/Q3)
[24].毛科技,吴旻媛,黄亮,等.后向散射辅助无线供能网络中的节点间高吞吐量通信方案[J]. 传感技术学报, 2021,34(1):103-108.
[25].毛科技,吴旻媛,池凯凯.无线供能网络中的节点间高吞吐量通信方案[J]. 传感技术学报, 2020,33(4):564-570.
[26].Chen L, Zhou X, Wang M , Keji M,et al. ARU-Net: Research and Application for Wrist Reference Bone Segmentation[J]. IEEE Access, 2019, 7(1):166930-166938.SCI,(IF:3.47/Q2)通信作者
[27].戴光麟, 杨志凯, 周贤年,陈立建,毛科技. WSN中一种流水式栅栏调度算法的研究[J]. 传感技术学报, 2019, 32(04):598-602.通信作者
[28].毛科技, 杨志凯.无线传感器网络中节点高精度定位算法的设计[M].上海交通大学出版社,2018
[29].陈立建, 毛科技.物联网若干关键技术研究[M].上海交通大学出版社,2018
[30].戴国勇,施伟元,应可珍,陈庆章,毛科技. 基于移动节点二次部署的WSN栅栏新型强化方法[J]. 电信科学, 2017,33(8):88-104.通信作者
[31].毛科技, 邬锦彬, 金洪波,等. 面向非视距环境的室内定位算法[J]. 电子学报, 2016, 44(5):1174-1179. EI:20162302471534
[32].毛科技, 方凯, 戴国勇,等. 采用Kriging的WSN多维度向量指纹定位算法研究[J]. 小型微型计算机系统, 2016, 37(11):2514-2519.
[33].戴光麟, 方凯, 戴国勇, 徐慧,毛科技.入侵轨迹建模与WSN栅栏覆盖分段调度算法研究[J]. 传感技术学报, 2016, 29(5):745-750.通信作者
[34].戴光麟,方凯,方飞,戴国勇,夏明,宦若虹,毛科技. 基于集合最大流算法的WSN栅栏修复方法研究[J]. 传感技术学报, 2016, 29(11):1742-1746.通信作者
[35].毛科技, 方凯, 戴国勇,等. 基于改进蚁群算法的无线传感器网络栅栏覆盖优化研究[J]. 传感技术学报, 2015,28(7):1058-1065.
[36].毛科技, 金洪波, 苗春雨,等. 无线传感器网络中的节点位置验证方法[J]. 传感技术学报, 2015,28(6):850-857.
[37].毛科技,范聪玲, 叶飞,等. 基于支持向量机的无线传感器网络节点定位算法[J]. 计算机研究与发展, 2014, 51(11):2427-2436.EI:20144900285888
[38].Mao K, Shao Q, He W, et al. Beacon moving location algorithm in WSN[J]. International Journal of Sensor Networks, 2013, 14(2):82-91. SCI:227XR
[39].Mao K, Zhao X, Shao Q, et al. Data Storage Scheme Supporting for Multidimensional Query[J]. International Journal of Distributed Sensor Networks, 2013, 2013(3):140-154. SCI:153AP ,EI:20132416413862
[40].毛科技, 戴光麟, 夏明,等. 采用分层结构的WSN室内三维定位算法的研究和设计[J]. 小型微型计算机系统, 2013, 34(2):277-280.
[41].K Mao,M Xia,Z Tang, et al. Design and Implement of Adaptive Training System[J].Journal of Information Computational Science, 2012,9(6):1683-1694。EI:20122715200146
[42].毛科技, 赵小敏, 何文秀,等. WSN中基于区域划分的半自动DV-Hop定位算法[J]. 计算机科学, 2012, 39(3):39-42.
[43].毛科技, 赵小敏, 衣俊艳,等. 采用Hull树的贪婪地理位置路由算法的设计[J]. 传感技术学报, 2012, 25(7):1007-1013.
[44].Mao K,Zhao X, He W, et al. Area Division Based Semi-auto DV-Hop Localization Algorithm in IEEGS[C],FSKD2011,2011(4): 2249-2253.EI: 20114014401316
[45].毛科技,何文秀,赵小敏等.支持多维查询的数据存储策略的设计[J].软件学报, 22 (s1):13-22,2011。EI: 20114814570552
[46].毛科技, 赵小敏, 邵奔,等. 无线传感网络中基于共面度的三维定位算法研究与设计[J]. 传感技术学报, 2011, 24(10):1484-1488.
[47].毛科技, 赵小敏, 宦若虹,等. 基于散列值的以数据为中心路由协议[J]. 传感技术学报, 2010, 23(9):1308-1316.
[48].毛科技, 赵小敏, 王一娇,等. 高密度且信号涵盖范围不规则的WSN广播算法研究[J]. 计算机研究与发展, 2010, 47(S2):133-138.
[49].MAO K,WU J, CHEN Q. The design and implementation of case-based learning in adaptive learning[C],IWCSEI2009,2009:571-576.EI:20095312585740
[50].MAO K,YU M, CHEN Q. Using Data Ming to Discover one Course’s Most Adaptive Students[C],WISM-AICI2009,2009:242-245.EI:20101112763716