电子邮件: yanfeng.lv@ia.ac.cn
通信地址: 北京市中关村东路95号
邮政编码: 100190
招生信息
每年招收1-2名硕士研究生。
欢迎申请推免硕士,欢迎报考硕士研究生!(申请:“人工智能菁英班”)
欢迎报考人工智能学院 非全日制研究生!
邮箱:yanfeng.lv@ia.ac.cn
主要从事:类脑感认知、图像检测与识别、机器人多模态感知、机器人技能学习与发育等方面的研究。
具体研究工作:
1. 受脑启发的感知认知计算、类脑脉冲神经网络等研究;
2. 面向机器人、无人机的视觉检测、识别与跟踪算法研究和应用;
3. 基于强化学习、持续学习的机器人技能学习与发育研究;
要求:
计算机、自动化、软件、电子信息、通信、物联网、测控、数学等信息类相关专业;
有较强的学习能力和意愿;
有较强的编程和数学功底;
招生专业
081104--模式识别与智能系统(硕士生,中科院自动化所)
085400--电子信息(非全日制硕士,国科大人工智能学院)
研究领域
类脑感认知、类脑智能机器人、机器人视觉、图像识别与检测、多模态感知、机器人自主导航等方面的研究。
教育背景
学历
学位
工学博士学位
工作经历
工作简历
社会兼职
2020-09-01-今,工业与信息化部专家信息库, 成员
2019-10-31-今,中国自动化学会专业委员会, 委员
2017-12-30-今,北京市科技专家库, 成员
2017-01-01-今,国家自然科学基金, 评议专家
2016-06-30-今,中国自动化学会, 会员
2016-06-30-今,中国计算机学会, 会员
2015-01-01-今,IEEE Robotics and Automation Society, 会员
出版信息
[1]Yanfeng Lu, Jingwen Gao, Qian Yu, et.al, “A Cross-Scale and Illumination Invariance-Based Model for Robust Object Detection in Traffic Surveillance Scenarios,” IEEE Transactions on Intelligent Transportation Systems, 2023. 24(7): 6989-6999.
[2]Yanfeng Lu, Xu Yang, Hong Qiao, et.al, “A Novel Biologically-inspired Structural Model for Feature and Correspondence,” IEEE Transactions on Cognitive and Developmental Systems, 2023. 15(2): 844-854.
[3]Yanfeng Lu, Qian Yu, et.al, “Cross Stage Partial Connections based Weighted Bi-directional Feature Pyramid and Enhanced Spatial Transformation Network for Robust Object Detection,” Neurocomputing, 2022. 513: 70-82.
[4]Yanfeng Lu, Huazhen Zhang, et.al, “Dominant Orientation Patch Matching for HMAX,” Neurocomputing, 2016. 193:155-166.
[5]Yanfeng Lu, Weijie Zhao,“What will the robots be like in the future?” National Science Review, 2019. 6(5): 1059–1061.
[6]Yanfeng Lu, Taekoo Kang, et.al. “Enhanced hierarchical model of object recognition based on a novel patch selection method in salient regions,” Computer Vision, IET, 2015, 9(5): 663-672.
[7]Yanfeng Lu, Hong Qiao, Lihao Jia, et.al, “Image Recommendation based on a Novel Biologically Inspired Hierarchical Model,” Multimedia Tools and Applications, 2018, 77 (4):4323-4337.
[8]Yanfeng Lu, Lihao Jia, Hong Qiao, et.al, “Enhanced Biologically Inspired Model for Image Recognition Based on a Novel Patch Selection Method with Moment,” International Journal on Wavelet, Multiresolution, and Information Processing,2019,17(2), 1940007.
[9]Yanfeng Lu, Myotaeg Lim, et.al. “Extended Biologically Inspired Model for Object Recognition Based on Oriented Gaussian-Hermite Moment,” Neurocomputing, 2014. 139(2): 189-201.
[10]Yanfeng Lu, Hong Qiao, Yi Li, et.al, “A Novel Biologically Inspired Hierarchical Model for Image Recommendation,” 14th International Symposium on Neural Networks , Sapporo, Japan, 2017.
[11]Yanfeng Lu, Huazhen Zhang, Myotaeg Lim, et.al. “A Novel Patch Selection Method in Salient Regions of Object recognition,” 30th Korean Conference of Institute of Control, Robotics and Systems, Seoul, South Korea, 2015.4.22-4.25.
[12]Yanfeng Lu, Aixuan Zhang, Hong Qiao, et.al. “Multi-Scale Scene Text Detection Based on Convolutional Neural Network,” Chinese Automation Congress, 2019.
[13]Yanfeng Lu, Huazhen Zhang, Myotaeg Lim, et.al. Enhanced Hierarchical Model of Object Recognition Based on Saliency Map and Keypoint. Institute of Control, Robotics and Systems, 2015:53-54.
[14] Yi Li, Yanfeng Lu*, et.al. "Electromagnetic Force Analysis of a Power Transformer Under the Short-Circuit Condition," IEEE Transactions on Applied Superconductivity, 2021,31(8): 1-3.
[15]Yi Li, Yanfeng Lu*, et.al. Insulator defect detection for power grid based on light correction enhancement and YOLOv5 model, Energy Reports, 2022, 13(8): 807-814.
[16]Chao Ma, Yanfeng Lu*, “Distributed Nonsynchronous Event-triggered State Estimation of Genetic Regulatory Networks with Hidden Markovian Jumping Parameters”, Mathematical Biosciences and Engineering, 2022, 19(12): 13878-13910.
[17]商迪,吕彦锋*,乔红,“受人脑中记忆机制启发的增量目标检测方法”,计算机科学,2023, 50 (2): 267-274.
[18]Junpeng Wang,Yanfeng Lu*, et al. A novel CNN model for fine-grained classification with large spatial variants, International Conference on Intelligent Computing and Signal Processing, 2020.
[19]Huazhen Zhang,Yanfeng Lu, Taekoo Kang, et.al, “B-HMAX: A fast Binary Biologically Inspired Model for Object Recognition,” Neurocomputing. 2016. 218: 242-250.
[20]Wenyu Zhang,Yanfeng Lu*, et.al. “Convolutional Neural Networks on Apache Storm,” Chinese Automation Congress, 2019.
[21]Jiayi Chang,Yanfeng Lu*, et al. Long-distance tiny face detection based on enhanced YOLOv3 for unmanned system,International Conference on Intelligent Unmanned Systems,2020.
[22]Bochao Liu,Yanfeng Lu*, et al. Spiking Neuron Networks based Energy-Efficient Object Detection for Mobile Robot, Chinese Automation Congress, 2021.
[23]Yi Li,Yanfeng Lu*, Dynamic Electromagnetic Force Analysis of a Power Transformer with Regulated Windings, IEEE International Conference on Applied Superconductivity and Electromagnetic Devices, 2020.
[24]Zidong Sun, Yanfeng Lu*, Underwater attached organisms intelligent detection based on an enhanced YOLO, IEEE International Conference on Electrical Engineering, Big Data and Algorithms, 2022, 1118-1122.
[25]Doyoung Lee,Yanfeng Lu, Myotaeg Lim, et.al. "3-D Vision Based Local Obstacle Avoidance Method for Humanoid Robot," 2012 International Conference on Controls Automation and Systems, Jeju,South Korea, 2012.10.20-10.23.