检索结果-内蒙古大学图书馆

IEEE Transactions on Intelligent Vehicles 2024年 1-13页

作者： Cao, Yihong Zhang, Hui Lu, Xiao Xiao, Zheng Yang, Kailun Wang, Yaonan College of Computer Science and Electronic Engineering Hunan University Changsha China National Engineering Research Center of Robot Vision Perception and Control Technology School of Robotics Hunan University Changsha China College of Engineering and Design Hunan Normal University Changsha China

Domain adaptive semantic segmentation enables robust pixel- wise understanding in real-world driving scenes. Source-free domain adaptation, as a more practical technique, addresses the concerns of data privacy and storage limitations in typical unsupervised domain adaptation methods, making it especially relevant in the context of intelligent vehicles. It utilizes a well-trained source model and unlabeled target data to achieve adaptation in the target domain. However, in the absence of source data and target labels, current solutions cannot sufficiently reduce the impact of domain shift and fully leverage the information from the target data. In this paper, we propose an end-to-end source-free domain adaptation semantic segmentation method via Importance-Aware and Prototype-Contrast (IAPC) learning. The proposed IAPC framework effectively extracts domain-invariant knowledge from the well-trained source model and learns domain-specific knowledge from the unlabeled target domain. Specifically, considering the problem of domain shift in the prediction of the target domain by the source model, we put forward an importance-aware mechanism for the biased target prediction probability distribution to extract domain-invariant knowledge from the source model. We further introduce a prototype-contrast strategy, which includes a prototype-symmetric cross-entropy loss and a prototype-enhanced cross-entropy loss, to learn target intra-domain knowledge without relying on labels. A comprehensive variety of experiments on two domain adaptive semantic segmentation benchmarks demonstrates that the proposed end-to-end IAPC solution outperforms existing state-of-the-art methods. The source code is publicly available at https://***/yihong-97/Source-free-IAPC. IEEE

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

DexRepNet: Learning Dexterous Robotic Grasping Network with Geometric and Spatial Hand-Object Representations

DexRepNet: Learning Dexterous Robotic Grasping Network with ...

引用

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Qingtao Liu Yu Cui Qi Ye Zhengnan Sun Haoming Li Gaofeng Li Lin Shao Jiming Chen College of Control Science and Engineering Zhejiang University Hangzhou China Key Lab of CS&AUS Zhejiang Province College of Control Science and Engineering and the State Key Laboratory of Industrial Control Technology Zhejiang University Department of Computer Science National University of Singapore Singapore

Robotic dexterous grasping is a challenging problem due to the high degree of freedom (DoF) and complex contacts of multi-fingered robotic hands. Existing deep re-inforcement learning (DRL) based methods leverage human demonstrations to reduce sample complexity due to the high dimensional action space with dexterous grasping. However, less attention has been paid to hand-object interaction representations for high-level generalization. In this paper, we propose a novel geometric and spatial hand-object interaction representation, named DexRep, to capture object surface features and the spatial relations between hands and objects during grasping. DexRep comprises Occupancy Feature for rough shapes within sensing range by moving hands, Surface Feature for changing hand-object surface distances, and LocalGeo Feature for local geometric surface features most related to potential contacts. Based on the new representation, we propose a dexterous deep reinforcement learning method DexRepNet to learn a generalizable grasping policy. Experimental results show that our method outperforms baselines using existing representations for robotic grasping dramatically both in grasp success rate and convergence speed. It achieves a 93% grasping success rate on seen objects and higher than 80% grasping success rates on diverse objects of unseen categories in both simulation and real-world experiments.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Transferable Physical Adversarial Patch Attack for Remote Sensing Object Detection

Transferable Physical Adversarial Patch Attack for Remote Se...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Di Wang Wenxuan Zhu Ke Li Xiao Gao Pengfei Yang School of Computer Science and Technology Xidian University Xi’an China College of Information and Control Engineering Xi’an University of Architecture and Technology Xi’an China

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

Deep neural networks (DNNs) have been widely used in remote sensing but demonstrated to be vulnerable with adversarial examples. By adding elaborately designed perturbations on the clean images, DNNs may output wrong prediction. Research on adversarial attack contributes to the study of model robustness. However, previous methods mainly focus on white-box scenario or digital domain for classification tasks, while the vulnerability of remote sensing detectors has not been fully explored. Aiming at attacking black-box remote sensing detectors in physical domain, we propose to generate a transferable physical adversarial patch (TPAP) as the perturbations. Specifically, the initial patch is optimized by a U-Net and modified by the plane mask and position mask before applied to the clean image. By attacking a surrogate model, TPAP can be transferred to the target model. Abundant experimental results validate the attack ability of TPAP and evaluate the robustness of current one-stage detectors.

关键词： YOLO Perturbation methods Closed box Detectors Robustness Sensors Task analysis

来源：评论

学校读者我要写书评

暂无评论

Correction of Gamma Distortion in Fringe Projection by Compensation Image 4

Correction of Gamma Distortion in Fringe Projection by Compe...

引用

4th IEEE International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2022

作者： Zhang, Zhou Chen, Tianyun Liu, Zhanhao North China Electric Power University School of Control and Computer Engineering Beijing China Yanbian University College of Science Yanji China Wuhan Textiles University School of Electronic and Electrical Engineering Wuhan China

ISBN: (数字)9781665467667

ISBN: (纸本)9781665467667

In fringe projection profilometry, affected by the gamma distortion of the projector, the reconstructed topography of the measured object has a large error compared to the actual situation. In order to eliminate the gamma distortion error, this paper innovatively proposes a mathematical model to solve the wrapping phase with 3(N)+1 images based on the principle of the N-step phase-shift method. The model adds an image modulated by half of the background illumination with gamma distortion to the three-step phase-shifted image. After iteration, the wrapping phase can be solved, and the value of the background illumination and the value of the projector gamma distortion can be obtained. The method effectively avoids the influence of gamma distortion on solving the wrapped phase. It is verified by MATLAB simulation that the method can eliminate gamma distortion. Comparing the phases solved by the simulation standard conditions, the four-step phase-shift method, and the 3(N)+1 method, the results show that the method effectively eliminates the influence of gamma distortion and has high accuracy. © 2022 IEEE.

关键词： Iterative methods

来源：评论

学校读者我要写书评

暂无评论

A New Mutimodel approach for modelling of fractional order interval transfer functions 20

A New Mutimodel approach for modelling of fractional order i...

引用

20th International Multi-Conference on Systems, Signals and Devices, SSD 2023

作者： Talmoudi, Samia Ksouri, Moufida Lahmari Applied College Department of Computer Science University of Tabuk Tabuk Saudi Arabia University of Tunis El Manar National Engineering School of Tunis LR11ES20 Analysis Design and Control of Systems Laboratory Tunis1002 Tunisia

ISBN: (纸本)9798350332568

This paper is focused on uncertain fractional order systems. In this context, a new modelling approach of uncertain fractional order systems represented by an explicit fractional order interval transfer function is proposed. This approach is based, essentially, on multimodel approach. In fact, firstly, two new determination methods of models' library, inspired from the Kharitonov approach, are exposed. Then, we propose to compute the validity degree of each model of the obtained library, by optimizing a constrained least squares problem. The global model is, finally deduced by fusion of outputs of the different library' models. To prove its efficiency and its precision, the proposed approach is then compared to the approximation approach of Oustaloup through two simulation examples. © 2023 IEEE.

关键词： Transfer functions

来源：评论

学校读者我要写书评

暂无评论

Wireless Sensing for Material Identification: A Survey

引用

IEEE Communications Surveys and Tutorials 2024年

作者： Chen, Yande Xu, Chongzhi Li, Kexin Zhang, Jia Guo, Xiuzhen Jin, Meng Zheng, Xiaolong He, Yuan Tsinghua University School of Software Beijing China Beijing University of Posts and Telecommunications School of Computer Science Beijing China Shanghai Jiao Tong University John Hopcroft Center for Computer Science Shanghai China Zhejiang University College of Control Science and Engineering Hangzhou China

As an application of fine-grained wireless sensing, RF-based material identification follows the paradigm of RF computing that fetches the information during RF signal propagation. Specifically, the RF signal accesses the objects' material-related information and carries the information with its electromagnetic properties. With a variety of important applications, research on RF-based material identification has gained significant progress in recent years. However, several fundamental problems remain insufficiently studied, such as the sensing models, signal processing approaches, performance and future extensions. This paper presents the first comprehensive survey of RF-based material identification. According to the basic sensing model used for sensing, we propose a taxonomy to classify the existing works into two categories: reflection-based and penetration-based. The works in each category are further grouped by the type of RF signals used, with elaborated discussion of the detailed approaches and the common challenges. We provide a framework that benchmarks the performance of the existing works, followed by a thorough discussion of future extensions. © 1998-2012 IEEE.

关键词： II-VI semiconductors

来源：评论

学校读者我要写书评

暂无评论

HTPSeg: A Semantic Segmentation Database for House-Tree-Person Psychological Test

HTPSeg: A Semantic Segmentation Database for House-Tree-Pers...

引用

International Conference on Tools for Artificial Intelligence (ICTAI)

作者： Hao Wang Jin Wang Ting Pan Bingfeng Zhang Weifeng Liu Qingdao Institute of Software College of Computer Science and Technology China University of Petroleum (East China) Qingdao China College of Control Science and Engineering China University of Petroleum (East China) Qingdao China

ISBN: (数字)9798331527235

ISBN: (纸本)9798331527242

The House Tree Person (HTP) test is widely recommended for clinical application of mental illness. Traditionally, therapists assess a patient's mental state by analyzing the content of their HTP drawings manually, which is time-consuming and susceptible to the therapist's subjective influences. Recently, using intelligent diagnostic models to tackle HTP test has attracted much attention. However, most existing models attempt to make a binary classification for HTP drawings, i.e., positive or negative psychological states, making details that can reflect the psychological state of the patient lost. To address the above challenge, in this paper, we introduce the semantic segmentation task into the HTP test for the first time to generate pixel-level semantic information. We first construct a semantic segmentation dataset about HTP psychological diagnosis named HTPSeg. Subsequently, to overcome the domain gap between HTP drawings and natural images, we propose to use the Low-Rank Adaptation (LoRA) fine-tuning strategy to adapt the Segment Anything Model (SAM) to the task of HTP drawing analysis. Specifically, we integrate the rank decomposition matrices into the projection layer of the transformer block in SAM's image encoder for fine-tuning. Additionally, we freeze the Mask Decoder and fine-tune the Prompt Encoder using default embeddings. Extensive experiments indicate the effectiveness and efficiency of the proposed method. The dataset and code will be available at https://***/clown06/HTPSeg.

关键词： Analytical models Adaptation models Heavily-tailed distribution Semantic segmentation Computational modeling Semantics Psychology Feature extraction Transformers Matrix decomposition

来源：评论

学校读者我要写书评

暂无评论

Fault-Tolerant Multi-Robot Target Pursuit with Fault Detection and Isolation Based on Mobile Adaptive Networks 11

Fault-Tolerant Multi-Robot Target Pursuit with Fault Detecti...

引用

11th IEEE Annual International Conference on CYBER Technology in Automation, control, and Intelligent Systems, CYBER 2021

作者： You, Jia Li, Zhenhui Yang, Jianhua College of Information Science and Electronic Engineering Zhejiang University Hangzhou China College of Control Science and Engineering Zhejiang University Hangzhou China College of Computer Science and Technology Zhejiang University Hangzhou China

ISBN: (纸本)9781665425278

Multi-robot target pursuit is a typical problem in multi-robot systems and can be solved by mobile adaptive networks in distributed way. For the importance and difficulty in improving fault tolerance of multi-robot systems, many adaptations of mobile adaptive networks have emerged. This paper introduces fault detection and isolation to the standard (with the weighted average aggregation rule) and three existed adaptations (with the coordinate-wise median, geometric median, and centerpoint aggregation rules) of mobile adaptive networks, which uses the differences of the theoretical estimated values and the actual estimated values to predict normal neighbor set in mobile adaptive networks, and carries out target pursuit. Fault-tolerant multi-robot target pursuit algorithms with fault detection and isolation based on mobile adaptive networks are proposed to remove the interference of the faults in the networks to achieve better performance in target pursuit. Simulation experiments have been carried out with different numbers of faulty robots in the original algorithms and our improved algorithms. Our proposed algorithms are proved to perform better in convergence and accuracy than the original algorithms, especially when the number of faulty robots increases, and the improvement effects on target pursuit algorithms with different aggregation rules can be different. © 2021 IEEE.

关键词： Multipurpose robots

来源：评论

学校读者我要写书评

暂无评论

Asymptotic behavior of least squares estimators for nonlinear autoregressive models

引用

science China(Information sciences) 2023年第6期66卷 299-300页

作者： Zhaobo LIU Chanying LI College of Computer Science and Software Engineering Shenzhen University Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of Sciences School of Mathematical Sciences University of Chinese Academy of Sciences

Dear editor,Estimations of nonlinear autoregressive(AR) models in the literature typically involve ergodic series. Based on this assumption,the asymptotic theory has been established accordingly(see [1–3]). However,t...

关键词：

来源：评论

学校读者我要写书评

暂无评论

K-Means-Based Mobile Adaptive Networks for Swarm Robotic Systems with Non-Cooperative Behaviors 6

K-Means-Based Mobile Adaptive Networks for Swarm Robotic Sys...

引用

6th International Conference on Computational Intelligence and Applications, ICCIA 2021

作者： You, Jia Li, Zhenhui Yang, Jianhua Zhejiang University College of Information Science and Electronic Engineering Hangzhou China Zhejiang University College of Control Science and Engineering Hangzhou China Zhejiang University College of Computer Science and Technology Hangzhou China

ISBN: (纸本)9781665439336

Mobile adaptive networks enable distributed adaptation and learning over networks while maintaining the cooperative motion, and play an important role in multi-robot control. Non-cooperative behaviors are common in swarm robotic systems and can greatly affect the system performance through information transmission and fusion in mobile adaptive networks. Some adaptations of different aggregation rules have been emerged to improve fault tolerance in mobile adaptive networks. This paper proposes K-means-based mobile adaptive networks which use K-means clustering algorithm to detect the faulty neighbors with non-cooperative behaviors and carry out mobile adaptive networks depending on information of the normal neighbors. Simulations are carried out in four existed mobile adaptive networks with different aggregation rules and our K-means-based mobile adaptive networks with these four aggregation rules. Simulation results prove that our proposed algorithms have better fault tolerance than the original algorithms. © 2021 IEEE.

关键词： Adaptive control systems

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：