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TIPS: A three-dimensional phenotypic measurement system for individual maize tassel based on TreeQSM 期刊论文
ELSEVIER SCI LTD, 2023, 卷号: 212
作者:  Xu, Bo;  Wan, Xiangyuan;  Yang, Hao;  Feng, Haikuan;  Fu, Yuanyuan;  Cen, Haiyan;  Wang, Binbin;  Zhang, Zhoufeng;  Li, Siyuan;  Zhao, Chunjiang;  Yang, Guijun
Adobe PDF(13822Kb)  |  收藏  |  浏览/下载：62/0  |  提交时间：2023/10/10
Maize tassel  Organ -scale phenotypes  TreeQSM  Three-dimensional point cloud reconstruction  Digital photographs  
Unsupervised real image super-resolution via knowledge distillation network 期刊论文
COMPUTER VISION AND IMAGE UNDERSTANDING, 2023, 卷号: 234
作者:  Yuan, Nianzeng;  Sun, Bangyong;  Zheng, Xiangtao
Adobe PDF(6023Kb)  |  收藏  |  浏览/下载：68/0  |  提交时间：2023/08/14
Super-resolution  Knowledge distillation  Degradation module  Convolutional neural network  
Performance Assessment of Four Data-Driven Machine Learning Models: A Case to Generate Sentinel-2 Albedo at 10 Meters 期刊论文
REMOTE SENSING, 2023, 卷号: 15, 期号: 10
作者:  Chen, Hao;  Lin, Xingwen;  Sun, Yibo;  Wen, Jianguang;  Wu, Xiaodan;  You, Dongqin;  Cheng, Juan;  Zhang, Zhenzhen;  Zhang, Zhaoyang;  Wu, Chaofan;  Zhang, Fei;  Yin, Kechen;  Jian, Huaxue;  Guan, Xinyu
Adobe PDF(13289Kb)  |  收藏  |  浏览/下载：56/0  |  提交时间：2023/07/03
Sentinel-2  albedo  data-driven machine learning algorithms  remote sensing  
An Edge Computing Algorithm Based on Multi-Level Star Sensor Cloud 期刊论文
CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES, 2023, 卷号: 136, 期号: 2, 页码: 1643-1659
作者:  Ren, Siyu;  Qiu, Shi;  Cheng, Keyang
Adobe PDF(850Kb)  |  收藏  |  浏览/下载：96/0  |  提交时间：2023/04/07
Star-sensing  sensor cloud  fuzzy set  edge computing  mapping  
Dual Teacher: A Semisupervised Cotraining Framework for Cross-Domain Ship Detection 期刊论文
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2023, 卷号: 61
作者:  Zheng, Xiangtao;  Cui, Haowen;  Xu, Chujie;  Lu, Xiaoqiang
Adobe PDF(4542Kb)  |  收藏  |  浏览/下载：42/0  |  提交时间：2023/08/18
Index Terms- Cross-domain object detection  dual-teacher framework  semisupervised object detection  ship detection  teacher-student model