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Apple detection during different growth stages in orchards using the improved YOLOV3 model 期刊论文
Computers and Electronics in Agriculture, 2019, 期号: 157, 页码: 417-426
作者:  Tian YN(田雨农)
Adobe PDF(4028Kb)  |  收藏  |  浏览/下载：175/59  |  提交时间：2022/01/07
Apple images acquisition  Image augmentation  Deep learning  YOLOV3-dense  Real-time detection  
Detection of Apple Lesions in Orchards Based on Deep Learning Methods of CycleGAN and YOLOV3-Dense 期刊论文
Journal of Sensors, 2019, 期号: 2019, 页码: 1-13
作者:  Tian YN(田雨农)
Adobe PDF(26755Kb)  |  收藏  |  浏览/下载：178/40  |  提交时间：2022/01/06
optical sensors  deep learning  lesion detection  CycleGAN  DenseNet  YOLO-V3 model  
A Pedestrian Dead-Reckoning System for Walking and Marking Time Mixed Movement Using an SHSs Scheme and a Foot-Mounted IMU 期刊论文
IEEE Sensors Journal, 2019, 卷号: 19, 期号: 5, 页码: 1661-1671
作者:  Wu, Yuan;  Zhu, Haibing;  Du, Qingxiu;  Tang, Shuming
浏览  |  Adobe PDF(2054Kb)  |  收藏  |  浏览/下载：468/127  |  提交时间：2019/05/04
Pedestrian Dead-reckoning  Imu  Step And Heading System  Gait Partitioning  Motion Classification  Ekf Filtering  Marking Time  Trajectory Estimation  
Dynamic Identification of Critical Nodes and Regions in Power Grid Based on Spatio-Temporal Attribute Fusion of Voltage Trajectory 期刊论文
ENERGIES, 2019, 卷号: 12, 期号: 5, 页码: 16
作者:  Bai, Xiwei;  Liu, Daowei;  Tan, Jie;  Yang, Hongying;  Zheng, Hengfeng
浏览  |  Adobe PDF(3091Kb)  |  收藏  |  浏览/下载：392/58  |  提交时间：2019/04/23
critical node  critical region  spatio-temporal attribute fusion  node voltage trajectory  
StarCraft Micromanagement With Reinforcement Learning and Curriculum Transfer Learning 期刊论文
IEEE Transactions on Emerging Topics in Computational Intelligence, 2019, 卷号: 3, 期号: 1, 页码: 73-84
作者:  Kun Shao;  Yuanheng Zhu;  Dongbin Zhao
浏览  |  Adobe PDF(4125Kb)  |  收藏  |  浏览/下载：365/137  |  提交时间：2019/04/22
Reinforcement Learning, Transfer Learning, Curriculum Learning, Neural Network, Game Ai  
High-quality 3D Reconstruction with Depth Super-resolution and Completion 期刊论文
IEEE Access, 2019, 卷号: 7, 期号: 1, 页码: 19370-19381
作者:  Li JW(李建伟);  Gao W(高伟);  Wu YH(吴毅红)
浏览  |  Adobe PDF(4152Kb)  |  收藏  |  浏览/下载：371/104  |  提交时间：2019/04/22
Deep Learning  Super-resolution  Image Processing  Depth Completion  3d Reconstruction