中文版 | English

在结果中检索

CASIA OpenIR

浏览/检索结果: 共51条，第1-10条 帮助

限定条件                    
已选(0)清除 条数/页：   排序方式：
DLA+: A Light Aggregation Network for Object Classification and Detection 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 6, 页码: 963-972
作者:  Fu-Tian Wang;  Li Yang;  Jin Tang;  Si-Bao Chen;  Xin Wang
Adobe PDF(1212Kb)  |  收藏  |  浏览/下载：185/30  |  提交时间：2021/11/26
Light weight  image classification  channel attention  efficient convolution  object detection  
Supervised and Semi-supervised Methods for Abdominalm Organ Segmentation: A Review 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 6, 页码: 887-914
作者:  Isaac Baffour Senkyire;  Zhe Liu
Adobe PDF(1308Kb)  |  收藏  |  浏览/下载：218/48  |  提交时间：2021/11/26
Abdominal organ, supervised segmentation  semi-supervised segmentation  evaluation metrics  image segmentation  machine learning  
STRNet: Triple-stream Spatiotemporal Relation Network for Action Recognition 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 5, 页码: 718-730
作者:  Zhi-Wei Xu;  Xiao-Jun Wu;  Josef Kittler
Adobe PDF(1129Kb)  |  收藏  |  浏览/下载：174/44  |  提交时间：2021/09/13
Action recognition  spatiotemporal relation  multi-branch fusion  long-term representation  video classification  
Low-cost Position and Force Measurement System for Payload Transport Using UAVs 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 4, 页码: 594-604
作者:  Daniel Ceferino Gandolfo;  Claudio D. Rosales;  Lucio R. Salinas;  J. Gimenez;  Ricardo Carelli
Adobe PDF(5932Kb)  |  收藏  |  浏览/下载：122/37  |  提交时间：2021/07/20
Payload transport  unmanned aerial vehicle (UAV)  measurement system  path following controller  low-cost system  
Contrastive Self-supervised Representation Learning Using Synthetic Data 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 4, 页码: 556-567
作者:  Dong-Yu She;  Kun Xu
Adobe PDF(993Kb)  |  收藏  |  浏览/下载：182/41  |  提交时间：2021/07/20
Self-supervised learning  contrastive learning  synthetic image  convolutional neural network  representation learning  
Identification and classification of driving behaviour at a signalized intersection using support vector machine 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 3, 页码: 480-491
作者:  Soni Lanka Karri;  Liyanage Chandratilak De Silva;  Daphne Teck Ching Lai;  Shiaw Yin Yong
Adobe PDF(1497Kb)  |  收藏  |  浏览/下载：531/312  |  提交时间：2021/05/24
Signalized intersection  driving behaviour  machine learning  support vector machine (SVM)  road accidents  
Learning Deep RGBT Representations for Robust Person Re-identification 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 3, 页码: 443-456
作者:  Ai-Hua Zheng;  Zi-Han Chen;  Cheng-Long Li;  Jin Tang;  Bin Luo
Adobe PDF(1832Kb)  |  收藏  |  浏览/下载：261/54  |  提交时间：2021/05/24
Person re-identification (Re-ID)  thermal infrared  generative networks  attention  deep learning  
2D and 3D Palmprint and Palm Vein Recognition Based on Neural Architecture Search 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 3, 页码: 377-409
作者:  Wei Jia;  Wei Xia;  Yang Zhao;  Hai Min;  Yan-Xiang Chen
Adobe PDF(15758Kb)  |  收藏  |  浏览/下载：295/44  |  提交时间：2021/05/24
Performance evaluation  neural architecture search  biometrics  palmprint  palm vein  deep learning  
Deep Audio-Visual Learning: A Survey 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 3, 页码: 351-376
作者:  Hao Zhu;  Man-Di Luo;  Rui Wang;  Ai-Hua Zheng;  Ran He
Adobe PDF(1864Kb)  |  收藏  |  浏览/下载：196/38  |  提交时间：2021/05/24
Deep audio-visual learning  audio-visual separation and localization  correspondence learning  generative models  representation learning  
A Comprehensive Review on Group Activity Recognition in Videos 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 3, 页码: 334-350
作者:  Li-Fang Wu;  Qi Wang;  Meng Jian;  Yu Qiao;  Bo-Xuan Zhao
Adobe PDF(1415Kb)  |  收藏  |  浏览/下载：267/63  |  提交时间：2021/05/24
Group activity recognition (GAR)  human activity recognition  scene understanding  video analysis  computer vision