中文版 | English

在结果中检索

CASIA OpenIR

浏览/检索结果: 共6条，第1-6条 帮助

已选(0)清除 条数/页：   排序方式：
Physics-Based Modeling and Fluttering Dynamic Process Simulation for Catkins 期刊论文
FORESTS, 2023, 卷号: 14, 期号: 12, 页码: 28
作者:  Zhang, Jiaxiu;  Yang, Meng;  Xi, Benye;  Duan, Jie;  Huang, Qingqing;  Meng, Weiliang
收藏  |  浏览/下载：36/0  |  提交时间：2024/02/22
clustering  catkin modeling  wind field simulation  catkin control  
Sand painting conversion based on detail preservation 期刊论文
COMPUTERS & GRAPHICS-UK, 2023, 卷号: 115, 页码: 371-381
作者:  Zhu, Mengting;  Yang, Meng;  Meng, Weiliang;  Li, Ping
收藏  |  浏览/下载：34/0  |  提交时间：2023/11/17
Parameter optimization  Detail painting  Edge processing  
Deep Deformation Detail Synthesis for Thin Shell Models 期刊论文
COMPUTER GRAPHICS FORUM, 2023, 页码: 13
作者:  Chen, Lan;  Gao, Lin;  Yang, Jie;  Xu, Shibiao;  Ye, Juntao;  Zhang, Xiaopeng;  Lai, Yu-Kun
收藏  |  浏览/下载：104/0  |  提交时间：2023/11/17
Computing methodologies  Physical simulation  Artificial intelligence  
HTCViT: an effective network for image classification and segmentation based on natural disaster datasets 期刊论文
VISUAL COMPUTER, 2023, 页码: 13
作者:  Ma, Zhihao;  Li, Wei;  Zhang, Muyang;  Meng, Weiliang;  Xu, Shibiao;  Zhang, Xiaopeng
收藏  |  浏览/下载：98/0  |  提交时间：2023/11/17
Natural disaster image analysis  Vision transformer  Convolution  Hierarchical  
Triple-strip attention mechanism-based natural disaster images classification and segmentation 期刊论文
VISUAL COMPUTER, 2022, 卷号: 38, 期号: 2022, 页码: 3163-3173
作者:  Ma, Zhihao;  Yuan, Mengke;  Gu, Jiaming;  Meng, Weiliang;  Xu, Shibiao;  Zhang, Xiaopeng
Adobe PDF(4674Kb)  |  收藏  |  浏览/下载：378/98  |  提交时间：2022/07/25
Natural disaster image analysis  Image segmentation  Attention mechanism  
Progressive polarization based reflection removal via realistic training data generation 期刊论文
PATTERN RECOGNITION, 2022, 卷号: 124, 页码: 13
作者:  Pang, Youxin;  Yuan, Mengke;  Fu, Qiang;  Ren, Peiran;  Yan, Dong-Ming
Adobe PDF(4985Kb)  |  收藏  |  浏览/下载：304/39  |  提交时间：2022/02/16
Deep learning  Reflection removal  Polarization  Progressive network  Convolutional neural networks