CASIA OpenIR

浏览/检索结果: 共130条,第1-10条 帮助

限定条件                        
已选(0)清除 条数/页:   排序方式:
Input-to-state stability of impulsive switched systems involving uncertain impulse-switching moments 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 6, 页码: 1515-1517
作者:  Chang Liu;  Wenlu Liu;  Tengda Wei;  Xiaodi Li
Adobe PDF(486Kb)  |  收藏  |  浏览/下载:14/4  |  提交时间:2024/05/22
Adaptive Space Expansion for Fast Motion Planning 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 6, 页码: 1499-1514
作者:  Shenglei Shi;  Jiankui Chen
Adobe PDF(4194Kb)  |  收藏  |  浏览/下载:13/5  |  提交时间:2024/05/22
Adaptive space expansion (ASE)  hyper-ellipsoid ring  informed sampling  motion planning  
Accelerated Primal-Dual Projection Neurodynamic Approach with time Scaling for Linear and set Constrained Convex Optimization Problems 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 6, 页码: 1485-1498
作者:  You Zhao;  Xing He;  Mingliang Zhou;  Tingwen Huang
Adobe PDF(2287Kb)  |  收藏  |  浏览/下载:12/7  |  提交时间:2024/05/22
Accelerated projection neurodynamic approach  linear and set constraints  projection operators  smooth and nonsmooth convex optimization  time scaling  
Multiobjective Differential Evolution for Higher-Dimensional Multimodal Multiobjective Optimization 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 6, 页码: 1458-1475
作者:  Jing Liang;  Hongyu Lin;  Caitong Yue;  Ponnuthurai Nagaratnam Suganthan;  Yaonan Wang
Adobe PDF(2268Kb)  |  收藏  |  浏览/下载:3/2  |  提交时间:2024/05/22
Benchmark functions  diversity measure  evolutionary algorithms  multimodal multiobjective optimization  
The Journey/DAO/TAO of Embodied Intelligence: From Large Models to Foundation Intelligence and Parallel Intelligence 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 6, 页码: 1313-1316
作者:  Tianyu Shen;  Jinlin Sun;  Shihan Kong;  Yutong Wang;  Juanjuan Li;  Xuan Li;  Fei-Yue Wang
Adobe PDF(682Kb)  |  收藏  |  浏览/下载:4/1  |  提交时间:2024/05/22
Visual Semantic Segmentation Based on Few/Zero-Shot Learning: An Overview 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 5, 页码: 1106-1126
作者:  Wenqi Ren;  Yang Tang;  Qiyu Sun;  Chaoqiang Zhao;  Qing-Long Han
Adobe PDF(12695Kb)  |  收藏  |  浏览/下载:21/2  |  提交时间:2024/04/10
Computer vision  deep learning  few-shot learning  low-shot learning  semantic segmentation  zero-shot learning  
Evolutionary Optimization Methods for High-Dimensional Expensive Problems: A Survey 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 5, 页码: 1092-1105
作者:  MengChu Zhou;  Meiji Cui;  Dian Xu;  Shuwei Zhu;  Ziyan Zhao;  Abdullah Abusorrah
Adobe PDF(2100Kb)  |  收藏  |  浏览/下载:20/3  |  提交时间:2024/04/10
Evolutionary algorithm (EA)  high-dimensional expensive problems (HEPs)  industrial applications  surrogate-assisted optimization  
A Weakly-Supervised Crowd Density Estimation Method Based on Two-Stage Linear Feature Calibration 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 4, 页码: 965-981
作者:  Yong-Chao Li;  Rui-Sheng Jia;  Ying-Xiang Hu;  Hong-Mei Sun
Adobe PDF(10448Kb)  |  收藏  |  浏览/下载:35/16  |  提交时间:2024/03/18
Crowd density estimation  linear feature calibration  vision transformer  weakly-supervision learning  
Constrained Multi-Objective Optimization With Deep Reinforcement Learning Assisted Operator Selection 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 4, 页码: 919-931
作者:  Fei Ming;  Wenyin Gong;  Ling Wang;  Yaochu Jin
Adobe PDF(2091Kb)  |  收藏  |  浏览/下载:37/15  |  提交时间:2024/03/18
Constrained multi-objective optimization  deep Q-learning  deep reinforcement learning (DRL)  evolutionary algorithms  evolutionary operator selection  
A Tutorial on Federated Learning from Theory to Practice: Foundations, Software Frameworks, Exemplary Use Cases, and Selected Trends 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 4, 页码: 824-850
作者:  M. Victoria Luzón;  Nuria Rodríguez-Barroso;  Alberto Argente-Garrido;  Daniel Jiménez-López;  Jose M. Moyano;  Javier Del Ser;  Weiping Ding;  Francisco Herrera
Adobe PDF(4602Kb)  |  收藏  |  浏览/下载:32/10  |  提交时间:2024/03/18
Data privacy  distributed machine learning  federated learning  software frameworks