近期成果 |
[1]基于迭代RANSAC自适应新生目标强度估计的GM-PHD多目标跟踪方法,授权发明专利,ZL2015109431731; [2]基于RANSAC的直喷发动机单次喷油量液位高度视觉检测方法,授权发明专利,ZL2015109427191; [3]吴静静;宋淑娟;秦煜;安伟,基于mean shift的芯片X光图像层次分割,授权发明专利,ZL 201510943172.7; [4]吴静静;秦煜;宋淑娟;安伟,直喷发动机单次喷油量液位高度视觉测量修正方法,授权发明专利,ZL 201510942720.4 [5]秦煜,吴静静,基于RANSAC的激光网格标记图像特征提取(申请号201610184556.X) [6]秦煜,吴静静,基于双目视觉的电梯导轨自动测量系统(申请号201610184490.4) [7]宋淑娟,吴静静,一种改进的基于Meanshift的多通道图像分割算法(申请号CN201410818125.5) [8]吴静静,基于概率假设密度的目标数变化的视频跟踪算法(申请号CN201410779080.5) [9]吴静静,基于模拟退火优化BP神经网络的PH值预测方法(申请号CN201410738449.8) [10]吴静静,基于自适应新生目标强度的滤波算法(申请号CN201410737973.3) |
近期论文 |
[1]J.J.Wu,K. Li, andQ.J.Zhangetc, “Iterative RANSAC based adaptive birth intensity estimation in GM-PHD filter for multi-target tracking,” Signal Processing, 2017,131(2)(SCI) [2]J.J.Wu, S.Q.Hu, and Y. Wang,“Adaptive multifeature visual tracking in a Probability-hypothesis-density filtering framework,”Signal Processing, 2013, 93(12):2915-2926. (SCI) [3]J.J.Wu, S.Q.Hu, and Y. Wang,“Probability-hypothesis-density filter for multitarget visual tracking with trajectory recognition,”Optical Engineering, 2010, 49(12):129701-1-129701-9. (SCI) [4]J.J.Wu, L.H. You, and Y. Cao, “Particle Probability-Hypothesis-Density filter with Kernel Based State Extraction for Efficient Multi-target Visual Tracking, "Information Technology Journal, 2013, 12(17): 4176-4179.. (EI) [5]吴静静,尤丽华,安伟,等.基于概率假设密度的目标数变化视频跟踪算法.江苏大学学报:自然科学版, 2015(11),36(6):697-704.(CSCD) [6]吴静静,宋淑娟,安伟,周德强,张洪,一种基于mean shift的多通道图像分割算法.包装工程, 2015(21): 89-94.(CSCD) [7]吴静静,尤丽华,王瑶,宋淑娟,基于自适应新生目标强度的概率假设密度滤波. , 2015(11): 2741-2747.(CSCD) [8]L.H. You and J.J. Wu,“Generalized likelihood ratio detector for aluminum alloy defect detection,”Information Technology Journal, 2013, 12(18): 4447-4452. (EI) [9]Lihua You, Jingjing Wu etc.,“A statistical edge detection algorithm based on kalman filter ,”Journal of Investigative Medicine, 2014(12): 30-36. (SCI ) [10]L.H. You andJ.J. Wu, “Generalized likelihood ratio detector for aluminum alloy defect detection,”Information Technology Journal, 2013, 12(18): 4447-4452.(EI) |