检索结果-内蒙古大学图书馆

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

作者： Kairui Ding Boyuan Chen Ruihai Wu Yuyang Li Zongzheng Zhang Huan-Ang Gao Siqi Li Guyue Zhou Yixin Zhu Hao Dong Hao Zhao Institute for AI Industry Research (AIR) Tsinghua University Xingjian College Tsinghua University CFCS School of Computer Science Peking University Institute for Artificial Intelligence Peking University College of Control Science and Engineering Zhejiang University School of Vehicle and Mobility Tsinghua University

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Robotic manipulation with two-finger grippers is challenged by objects lacking distinct graspable features. Traditional pre-grasping methods, which typically involve repositioning objects or utilizing external aids like table edges, are limited in their adaptability across different object categories and environments. To overcome these limitations, we introduce PreAfford, a novel pre-grasping planning framework incorporating a point-level affordance representation and a relay training approach. Our method significantly improves adaptability, allowing effective manipulation across a wide range of environments and object types. When evaluated on the ShapeNet-v2 dataset, PreAfford not only enhances grasping success rates by 69% but also demonstrates its practicality through successful real-world experiments. These improvements highlight PreAfford’s potential to redefine standards for robotic handling of complex manipulation tasks in diverse settings.

关键词： Training Affordances Grasping Planning Relays Grippers Standards Intelligent robots

来源：评论

学校读者我要写书评

暂无评论

InterTracker: Discovering and Tracking General Objects Interacting with Hands in the Wild

InterTracker: Discovering and Tracking General Objects Inter...

引用

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

作者： Yanyan Shao Qi Ye Wenhan Luo Kaihao Zhang Jiming Chen College of Computer Science and Technology Zhejiang University of Technology Hangzhou China College of Control Science and Engineering Zhejiang University Hangzhou China School of Cyber Science and Technology Sun Yatsen University Shenzhen China College of Engineering Computing & Cybernetics Australian National University Canberra ACT Australia

Understanding human interaction with objects is an important research topic for embodied Artificial Intelligence and identifying the objects that humans are interacting with is a primary problem for interaction understanding. Existing methods rely on frame-based detectors to locate interacting objects. However, this approach is subjected to heavy occlusions, background clutter, and distracting objects. To address the limitations, in this paper, we propose to leverage spatio-temporal information of hand-object interaction to track interactive objects under these challenging cases. Without prior knowledge of the general objects to be tracked like object tracking problems, we first utilize the spatial relation between hands and objects to adaptively discover the interacting objects from the scene. Second, the consistency and continuity of the appearance of objects between successive frames are exploited to track the objects. With this tracking formulation, our method also benefits from training on large-scale general object-tracking datasets. We further curate a video-level hand-object interaction dataset for testing and evaluation from 100DOH. The quantitative results demonstrate that our proposed method outperforms the state-of-the-art methods. Specifically, in scenes with continuous interaction with different objects, we achieve an impressive improvement of about 10% as evaluated using the Average Precision (AP) metric. Our qualitative findings also illustrate that our method can produce more continuous trajectories for interacting objects.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Intelligent IoT-Aided Early Sound Detection of Red Palm Weevils

引用

computers, Materials & Continua 2021年第12期69卷 4095-4111页

作者： Mohamed Esmail Karar Omar Reyad Abdel-Haleem Abdel-Aty Saud Owyed Mohd F.Hassan College of Computing and Information Technology Shaqra UniversityShaqra11961Saudi Arabia Department of Industrial Electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityEgypt Faculty of Science Sohag UniversitySohag82524Egypt Department of Physics College of SciencesUniversity of BishaBisha61922Saudi Arabia Department of Mathematics College of SciencesUniversity of BishaBisha61922Saudi Arabia Department of Computer and Information Science CeRDaSUniversiti Teknologi PetronasMalaysia

Smart precision agriculture utilizes modern information and wireless communication technologies to achieve challenging agricultural ***,Internet of Things(IoT)technology can be applied to monitor and detect harmful insect pests such as red palm weevils(RPWs)in the farms of date palm *** this paper,we propose a new IoT-based framework for early sound detection of RPWs using fine-tuned transfer learning classifier,namely *** sound sensors,namely TreeVibes devices are carefully mounted on each palm trunk to setup wireless sensor networks in the *** trees are labeled based on the sensor node number to identify the infested ***,the acquired audio signals are sent to a cloud server for further on-line analysis by our fine-tuned deep transfer learning model,i.e.,*** proposed infestation classifier has been successfully validated on the public TreeVibes *** includes total short recordings of 1754 samples,such that the clean and infested signals are 1754 and 731 samples,*** to other deep learning models in the literature,our proposed InceptionResNet-V2 classifier achieved the best performance on the public database of TreeVibes audio *** resulted classification accuracy score was 97.18%.Using 10-fold cross validation,the fine-tuned InceptionResNet-V2 achieved the best average accuracy score and standard deviation of 94.53%and±1.69,*** the proposed intelligent IoT-aided detection system of RPWs in date palm farms is the main prospect of this research work.

关键词： Red palm weevils smart precision agriculture internet of things artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

A Consensus-Based Generalized Multi-Population Aggregative Game with Application to Charging Coordination of Electric Vehicles

arXiv

引用

arXiv 2023年

作者： Ghavami, Mahsa Bakhshayesh, Babak Ghaffarzadeh Haeri, Mohammad Como, Giacomo Kebriaei, Hamed The Advanced Control Systems Lab Department of Electrical Engineering Sharif University of Technology Tehran Iran School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran The Department of Mathematical Sciences Politecnico di Torino Torino Italy

This paper introduces a consensus-based generalized multi-population aggregative game coordination approach with application to electric vehicles charging under transmission line constraints. The algorithm enables agents to seek an equilibrium solution while considering the limited infrastructure capacities that impose coupling constraints among the users. The Nash-seeking algorithm consists of two interrelated iterations. In the upper layer, population coordinators collaborate for a distributed estimation of the coupling aggregate term in the agents’ cost function and the associated Lagrange multiplier of the coupling constraint, transmitting the latest updated values to their population’s agents. In the lower layer, each agent updates its best response based on the most recent information received and communicates it back to its population coordinator. For the case when the agents’ best response mappings are non-expansive, we prove the algorithm’s convergence to the generalized Nash equilibrium point of the game. Simulation results demonstrate the algorithm’s effectiveness in achieving equilibrium in the presence of a coupling constraint. © 2023, CC BY-NC-ND.

关键词： Electric vehicles

来源：评论

学校读者我要写书评

暂无评论

Sentiment Classification of Chinese Railway Review Text Based on Multi-Feature Fusion Gated Recurrent Unit

Sentiment Classification of Chinese Railway Review Text Base...

引用

2021 International Conference on Information Science, Parallel and Distributed Systems, ISPDS 2021

作者： Su, Chenglang Jiang, Lekang Pi, Shaorui Shenzhen University College of Mechatronics and Control Engineering Shenzhen China University of Nottingham Department of Computer Science Nottingham United Kingdom University of Liverpool Department of Electrical Engineering and Electronics Liverpool United Kingdom

ISBN: (纸本)9781665417389

Posting comments through online platforms has become the main channel for many users to express their opinions. Many Chinese private companies have rectified their marketing strategies by collecting online user comments and using them as a reference. However, since many Chinese state-owned enterprises are within the system, they can only rectify and reform according to the plan provided by the government but with little effect. China's railway system is faced with such problems. Traditional sentiment classification methods may encounter some problems when processing short texts. Our research provides a Gated Recurrent Unit (GRU) sentiment classification method based on multi-feature fusion and sentiment classification of user reviews about China's railway system. And through classification, we get 1244 comments with negative emotions and 919 non-emotional comments © 2021 IEEE.

关键词： Railroads

来源：评论

学校读者我要写书评

暂无评论

Recognition of Pedestrians’ Crossing Intentions with a Conv-Transformer Network 8th

Recognition of Pedestrians’ Crossing Intentions with a Conv...

引用

8th International Conference on Artificial Intelligence and Security , ICAIS 2022

作者： Yang, Biao Yan, Guocheng Wang, Fujun Yang, Changchun Liu, Xiaofeng College of IoT Engineering Hohai University Changzhou213100 China School of Microelectronics and Control Engineering Changzhou University Changzhou213100 China School of Computer Science and Artificial Intelligence Changzhou University Changzhou213100 China Graduate School of Environment and Information Sciences YOKOHAMA National University Yokohama240-8501 Japan

ISBN: (纸本)9783031067662

Recognizing pedestrians’ crossing intentions is critical for self-driving cars to avoid vehicle-pedestrian collisions. However, it is challenging to recognize pedestrians’ crossing intentions based on their appearance or actions under severe conditions, including occlusions, dim illumination, and pedestrians standing far away. In this work, a Conv-transformer network is proposed to recognize pedestrians’ crossing intentions. Pedestrians’ appearance is modeled by a Resnet network, which will output a feature sequence describing pedestrians at different time steps. A Transformer network is then introduced to model the feature sequence to output the recognition result, which is crossing or not crossing. Evaluations on benchmarking databases, including JAAD and PIE, are performed. Results show that the proposed method can recognize pedestrians’ crossing intentions precisely. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Pedestrian safety

来源：评论

学校读者我要写书评

暂无评论

Exploring Gender Differences in EEG-Based Emotion Recognition with Haptic Vibration

Exploring Gender Differences in EEG-Based Emotion Recognitio...

引用

IEEE International Conference on Development and Learning, ICDL

作者： Xin Wang Baoguo Xu Jiajin Wang Wenbin Zhang Aiguo Song The State Key Laboratory of Digital Medical Engineering Jiangsu Key Laboratory of Remote Measurement and Control School of Instrument Science and Engineering Southeast University Nanjing China College of Computer and Information Hohai University Nanjing China

The study of gender differences in emotions has attracted interest in psychology and neuroscience for decades. However, gender differences in the emotions evoked by haptic stimuli still need to be investigated further. In this paper, we applied visual-auditory-haptic fusion stimuli to evoke four target emotions (joy, sadness, fear, and neutral), and the electroen-cephalogram (EEG) signals were recorded synchronously. The differential entropy (DE) feature was extracted, and the support vector machine (SVM) was employed for emotion classification. Experimental results indicated that females generally behaved with lower brain activation changes than males in most frequency bands and brain regions. Meanwhile, haptic stimuli improved emotion classification accuracy, especially for females. In addition, females showed greater individual differences than males, and haptic stimuli reduced the differences in the same gender, particularly in males. This research promises to facilitate the application of emotion recognition in haptic interactions.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Service Function Chain Dynamic Scheduling in Space-Air-Ground Integrated Networks

arXiv

引用

arXiv 2025年

作者： Jia, Ziye Cao, Yilu He, Lijun Wu, Qihui Zhu, Qiuming Niyato, Dusit Han, Zhu College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing211106 China State Key Laboratory of ISN Xidian University Xian710071 China School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 China School of Computer Science and Engineering Nanyang Technological University Singapore639798 Singapore Department of Electrical and Computer Engineering the University of Houston HoustonTX77004 United States Department of Computer Science and Engineering Kyung Hee University Seoul446-701 Korea Republic of

As an important component of the sixth generation communication technologies, the space-air-ground integrated network (SAGIN) attracts increasing attentions in recent years. However, due to the mobility and heterogeneity of the components such as satellites and unmanned aerial vehicles in multilayer SAGIN, the challenges of inefficient resource allocation and management complexity are aggregated. To this end, the network function virtualization technology is introduced and can be implemented via service function chains (SFCs) deployment. However, urgent unexpected tasks may bring conflicts and resource competition during SFC deployment, and how to schedule the SFCs of multiple tasks in SAGIN is a key issue. In this paper, we address the dynamic and complexity of SAGIN by presenting a reconfigurable time extension graph and further propose the dynamic SFC scheduling model. Then, we formulate the SFC scheduling problem to maximize the number of successful deployed SFCs within limited resources and time horizons. Since the problem is in the form of integer linear programming and intractable to solve, we propose the algorithm by incorporating deep reinforcement learning. Finally, simulation results show that the proposed algorithm has better convergence and performance compared to other benchmark algorithms. Copyright © 2025, The Authors. All rights reserved.

关键词： Network function virtualization

来源：评论

学校读者我要写书评

暂无评论

Industrial Data Extraction Method Based on Correlation Matrix and Multidimensional Probability Distribution 6

Industrial Data Extraction Method Based on Correlation Matri...

引用

6th International Conference on Power and Renewable Energy, ICPRE 2021

作者： Peng, Su Yue, Sun Zhihong, Luo China Ship Development and Design Center Wuhan China Harbin Engineering University College of Intelligent Systems Science and Engineering Harbin China North China Electric Power University School of Control and Computer Engineering Beijing China

ISBN: (纸本)9781665449618

The operation data of power plant has the characteristics of multivariable and big data, which is widely used in the research of data-driven modeling. Effective data extraction is an important part of data-driven modeling, and the performance of data extraction algorithm directly affects the accuracy of modeling. In this paper, an effective data extraction method based on correlation matrix and vine structure is proposed. The rank correlation coefficient is used to measure the correlation between variables and construct the correlation matrix. According to the correlation matrix, important variables are selected and grouped. Vine structure is used to establish a multi-dimensional joint distribution model for each group of variables. The data with high probability are extracted by confidence interval as effective data. Finally, the extracted results of multiple combinations are combined to form an effective data set. The SCR data are used for example verification, and the results show that the proposed method can extract effective data and improve the correlation between variables significantly. © 2021 IEEE.

关键词： Data mining

来源：评论

学校读者我要写书评

暂无评论

Selected Sample Retraining Semi-supervised Learning Method for Aerial Scene Classification 1st

Selected Sample Retraining Semi-supervised Learning Method f...

引用

1st CAAI International Conference on Artificial Intelligence, CICAI 2021

作者： Tian, Ye Li, Ju Zhang, Liguo Sun, Jianguo Yin, Guisheng College of Computer Science and Technology Harbin Engineering University Harbin150001 China China Industrial Control Systems Cyber Emergency Response Team Beijing100040 China

ISBN: (纸本)9783030930455

The performance of scene classification for remote sensing images based on deep neural networks is limited by the number of labeled data. To alleviate this problem, a variety of methods have been proposed to apply semi-supervised learning to exploit both labeled and unlabeled samples for training classifiers, but most of them still require a certain number of labeled samples considering the complex context relationship and huge spatial differences of remote sensing images. In this paper, we proposed a novel selected sample retraining semi-supervised learning method (S2 R) that is simple but works efficiently on scene classification remote sensing. First, we train several models independently, each model is trained for only a few epochs, and use them to label samples in the unlabeled data set. Then, the labeled unlabeled data set is divided into low-noise labeled data set and sub-unlabeled data set through the high probability sample selection method. Finally, the two segmented data sets are combined with the labeled data sets to train a scene classifier based on the semi-supervised learning method. To verify the effectiveness of the proposed method, it is further compared with several state-of-the-art semi-supervised classification approaches. The results demonstrate that our method consistently outperforms the previous methods on the condition of only a few labeled samples over the scene classification for remote sensing images. © 2021, Springer Nature Switzerland AG.

关键词： Remote sensing

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：