CASIA OpenIR

浏览/检索结果: 共38条,第1-10条 帮助

限定条件    
已选(0)清除 条数/页:   排序方式:
A 2D Mapping Method Based on Virtual Laser Scans for Indoor Robots 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 5, 页码: 747-765
作者:  Xu-Yang Shao;  Guo-Hui Tian;  Ying Zhang
Adobe PDF(2637Kb)  |  收藏  |  浏览/下载:196/44  |  提交时间:2021/09/13
2D mapping  indoor robots  virtual laser  mapping auxiliary strategies  safe navigation  
A Review on Cooperative Robotic Arms with Mobile or Drones Bases 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 4, 页码: 536-555
作者:  Larona Pitso Ramalepa;  Rodrigo S. Jamisola Jr.
Adobe PDF(1192Kb)  |  收藏  |  浏览/下载:481/338  |  提交时间:2021/07/20
Cooperative arms  mobile manipulator  aerial manipulator  mobile base  drone base  cooperative tasks  
PokerNet: Expanding Features Cheaply via Depthwise Convolutions 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 3, 页码: 432-442
作者:  Wei Tang;  Yan Huang;  Liang Wang
Adobe PDF(1163Kb)  |  收藏  |  浏览/下载:215/32  |  提交时间:2021/05/24
Deep learning  depthwise convolution  lightweight deep model  model compression  model acceleration  
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:278/42  |  提交时间:2021/05/24
Performance evaluation  neural architecture search  biometrics  palmprint  palm vein  deep 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:263/62  |  提交时间:2021/05/24
Group activity recognition (GAR)  human activity recognition  scene understanding  video analysis  computer vision  
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:192/36  |  提交时间:2021/05/24
Deep audio-visual learning  audio-visual separation and localization  correspondence learning  generative models  representation learning  
Suction-based Grasp Point Estimation in Cluttered Environment for Robotic Manipulator Using Deep Learning-based Affordance Map 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 2, 页码: 277-287
作者:  Tri Wahyu Utomo, Adha Imam Cahyadi, Igi Ardiyanto
Adobe PDF(913Kb)  |  收藏  |  浏览/下载:146/53  |  提交时间:2021/04/22
Grasping point estimation  household objects  red, green, blue and depth (RGBD) channel image  semantic segmentation  cluttered environment  
Hybrid Approach to Document Anomaly Detection: An Application to Facilitate RPA in Title Insurance 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 1, 页码: 55-72
作者:  Abhijit Guha;  Debabrata Samanta
Adobe PDF(1485Kb)  |  收藏  |  浏览/下载:192/53  |  提交时间:2021/02/23
Anomaly detection  title insurance  autoencoder  one-class support vector machine (OSVM)  term frequency – inverse document frequency (TF-IDF)  robotic process automation  dimensionality reduction  
Knowing Your Dog Breed: Identifying a Dog Breed with Deep Learning 期刊论文
International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 1, 页码: 45-54
作者:  Punyanuch Borwarnginn;  Worapan Kusakunniran;  Sarattha Karnjanapreechakorn;  Kittikhun Thongkanchorn
Adobe PDF(1149Kb)  |  收藏  |  浏览/下载:188/67  |  提交时间:2021/02/23
Computer vision  deep learning  dog breed classification  transfer learning  image augmentation  
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:208/47  |  提交时间:2021/11/26
Abdominal organ, supervised segmentation  semi-supervised segmentation  evaluation metrics  image segmentation  machine learning