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检索条件"机构=Key Lab. of Networked Control Systems"

共 271 条记录，以下是1-10 订阅

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Alzheimer's Disease Detection Based on Features Level Selection for CNN-SVM Combination

Alzheimer's Disease Detection Based on Features Level Select...

引用

2023 IEEE International Conference on Artificial Intelligence and Green Energy, ICAIGE 2023

作者： Zayene, Mohamed Amine Basly, Hend Sayadi, Fatma Ezahra National School of Engineering School of Sousse Lab. Networked Objects Control and Communication Systems Sousse Tunisia

ISBN: (纸本)9798350325539

Neurodegenerative disease especially dementia are reported as disease that leads to death, Alzheimer's Disease (AD) is kind dementia that cause progressive and irreversible brain disorder loss which leads to death. AD shows no symptoms in its early stages which makes diagnosing it its beginning a challenge and helpful for doctors as they can slow down its progress in its early stages. Computer-aided approaches such as machine learning which come up with several techniques to detect AD by extracting features from the given image data and use them to build a classifier. Recently, a subcategory of machine learning called deep learning has widely been employed to enhance the medical diagnosis by attempting notable performance. In fact, these approaches avoid the tricky manual feature extraction using Convolutional Neural Network (CNN) considered as a reference in the field of computer vision. This paper proposes a combination of machine-deep learning technics for early diagnosis of AD from positron emission tomography (PET). We first train our CNN on PET images to extract the most relevant features, then we select the most appropriate CNN's level from where the features will be extracted, which will be feed in a second step as input to a Support Vector Machine based classifier (SVM). The proposed approach achieves notable results that exceeded the performance obtained by various existing approaches. © 2023 IEEE.

关键词： Positron emission tomography

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An Improved RGB-D SLAM Method Based on Manhattan World and Point-Line-Plane Features 7

An Improved RGB-D SLAM Method Based on Manhattan World and P...

引用

2022 7th International Seminar on Computer Technology, Mechanical and Electrical Engineering, ISCME 2022

作者： Yang, Dehua Pei, Hailong Weng, Zhuorong Key Lab. of Autonomous Systems and Networked Control Ministry of Education Unmanned Aerial Vehicle Systems Eng. Tech. Research Center of Guangdong China South China University of Technology Guangzhou510640 China

At present, most feature-based SLAM methods are based on feature points. But in indoor environments where texture is scarce and light varies greatly, these methods will reduce the accuracy of pose estimation or even lead to pose tracking failure. To tackle the above problem, we propose an improved RGB-D SLAM method which employs point-line-plane feature extraction and matching as well as Manhattan Frames-based rotation estimation. Finally, the proposed method is proven to have good reliability and robustness in open datasets and real indoor scenes. © Published under licence by IOP Publishing Ltd.

关键词： Textures

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The DAO to Social Transportation: Towards Smart Mobility in Cyber-Physical-Social Space

The DAO to Social Transportation: Towards Smart Mobility in ...

引用

2023 IEEE International Conference on systems, Man, and Cybernetics, SMC 2023

作者： Chen, Yuanyuan Lv, Yisheng Wang, Fei-Yue Institute of Automation State Key Lab. of Multimodal Artificial Intelligence Systems Chinese Academy of Sciences Beijing100190 China Chinese Academy of Sciences State Key Lab. for Management and Control of Complex Systems Beijing100190 China

ISBN: (纸本)9798350337020

The rapid advancement of intelligence and connectivity technology (ICT) has enhanced the efficiency and safety of intelligent transportation systems (ITS). However, this also increases the complexity of the transportation systems, especially the social complexity, and poses new challenges for their management. This paper discusses the emergence of social transportation, as part of natural evolutionary adaptation to new traffic conditions and technology, which is a paradigm shift from engineering-centered technical systems to society-centered ecosystems. In social transportation systems, all participants including administrators, individual travelers and other stakeholders play a more proactive role in the operation and management of transportation systems. Therefore, we propose to employ a decen-tralized autonomous organization (DAO) as a model for the social transportation system that allows participants to collab.rate and coordinate without relying on a central authority. To meet the challenges brought by this transition, we propose to apply ACP-based parallel system theory to restructure the methodology of transportation management. Finally, we present a case study of personal carbon trading system where economic incentives are used to manage traffic demand, affecting others' travel behaviors, and reduce carbon emissions. In the conclusive remarks, we provide our visions and future directions of social transportation systems. © 2023 IEEE.

关键词： block chain cyber-physical-social system decentralized and autonomous organization social transportation

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A Vision-Based Autonomous Landing Method on Mobile Platform for UAV 42

A Vision-Based Autonomous Landing Method on Mobile Platform ...

引用

42nd Chinese control Conference, CCC 2023

作者： Zhu, Yongbin Pei, Hailong Wang, Liping Huang, Yuyuan Ou, Kangqi Ministry of Education Unmanned Aerial Vehicle Systems Eng.Tech. Research Center of Guangdong College of Automation Science and Engineering Key Lab of Autonomous Systems and Networked Control South China University of Technology Guangzhou510640 China

ISBN: (纸本)9789887581543

As the application scenarios of multi-rotor Unmanned Aerial Vehicles (UAVs) become more and more extensive, the field of target tracking and accurate landing has become one of the research hotspots. In order to realize the accurate autonomous landing of UAV, considering the increasingly mature visual navigation technology, this paper proposed a hierarchical landmark based on nested rectangles and its relative positioning algorithm, and designed a set of autonomous landing system for the mobile platform of quadrotor UAV. The landmark has a high recognition rate of different heights and good expansibility. The algorithm has high computational efficiency and low performance requirements for image processing equipment, thus the system has good accuracy and robustness. The simulation and flight experiment show that the proposed algorithm can effectively realize the accurate autonomous landing of UAV. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Object detection

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An FPGA-SoC based Hardware Acceleration of Convolutional Neural Networks 9

An FPGA-SoC based Hardware Acceleration of Convolutional Neu...

引用

9th IEEE International Conference on Sciences of Electronics, Technologies of Information and Telecommunications, SETIT 2022

作者： Bouaafia, Soulef Messaoud, Seifeddine Khemiri, Randa Sayadi, Fatma Ezahra Monastir University Lab. Electronics and Microelectronics Faculty of Sciences of Monastir Monastir Tunisia Sousse University Lab. Networked Objects Control and Communication Systems National Engineering School of Sousse Sousse Tunisia

ISBN: (数字)9781728184425

ISBN: (纸本)9781728184425

Deep learning has evolved as a discipline that has demonstrated its capacity and usefulness in tackling complicated learning issues as a result of recent improvements in digital technology and the availab.lity of authentic data. Convolutional neural networks (CNNs) in particular have demonstrated their usefulness in image processing and computer vision applications. They do, however, need heavy CPU operations and memory bandwidth, which prevents general-purpose CPUs from attaining desirable performance levels. To boost CNN throughput, hardware accelerators such as application-specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), and graphics processing units (GPUs) have been deployed. FPGAs, in particular, have lately been used to accelerate the development of deep learning networks due to their ability to optimize parallelism and power efficiency. Based on hardware-software architecture, this research provides a CNN acceleration model for video compression applications. Vivado High Level Synthesis is used to accelerate the CNN model in order to develop Intellectual Property (IP) cores. © 2022 IEEE.

关键词： Convolutional neural networks

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Alzheimer's Disease Detection Based on Features Level Selection for CNN-SVM Combination

Alzheimer's Disease Detection Based on Features Level Select...

引用

Artificial Intelligence & Green Energy (ICAIGE), IEEE International Conference on

作者： Mohamed Amine Zayene Hend Basly Fatma Ezahra Sayadi Lab. Networked Objects Control and Communication Systems National School of Engineering School of Sousse Sousse Tunisia

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Efficient Mobile Deployment of Lightweight CNN-Transformer Model for Crop Disease Diagnosis in Smart Agriculture 4

Efficient Mobile Deployment of Lightweight CNN-Transformer M...

引用

4th Asia Conference on Information Engineering, ACIE 2024

作者： Lv, Zirong China University of Geosciences Hubei Key Lab. of Adv. Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Automation Wuhan China

ISBN: (纸本)9798350371925

Crop disease diagnosis is of great significance for crop yield and agricultural production. Deep learning methods have become a major research direction for solving crop disease diagnosis. However, recent studies have shown that deploying complex neural network models on mobile devices poses a significant challenge to mobile hardware performance. To address this issue, this paper proposes a lightweight network model based on the Transformer and deploys it on mobile devices. Compared to other lightweight network models, our approach significantly reduces computational complexity using Transformer modules and exhibits a particular advantage in recognition accuracy. It achieves a recognition rate of 97.76% for ten categories of tomato diseases, while the model size is only 3.86 MB. Furthermore, we deploy the model on embedded devices and apply it to tomato crop recognition, enabling farmers to monitor crop conditions in real-time and realizing smart agriculture. © 2024 IEEE.

关键词： Deep learning

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Extended State Observer Based Fault-Tolerant Predictive control for a Four-Mecanum Wheels Mobile Robot 14

Extended State Observer Based Fault-Tolerant Predictive Cont...

引用

14th IEEE International Conference on Cyber Technology in Automation, control, and Intelligent systems, CYBER 2024

作者： Yang, Binghao Wang, Dongliang Wen, Ziling Wei, Wu Li, Wenji Fan, Zhun Shantou University Key Lab of Digital Signal and Image Processing of Guangdong Province Guangdong 515063 China Shantou University School of Department of Electronic and Information Engineering Guangdong 515063 China Key Laboratory of Autonomous Systems and Networked Control Ministry of Education Guangdong Guangzhou510640 China School of Automation Science and Engineering South China University of Technology Guangdong Guangzhou510641 China

ISBN: (纸本)9798331506056

The application of unmanned vehicles in industrial cargo transportation is becoming increasingly widespread, particularly playing a significant role in transporting heavy-duty goods. However, when performing such tasks, whether in single-vehicle transportation or multi-vehicle collab.rative transportation, the occurrence of wheel failures can potentially lead to serious safety accidents. Therefore, this paper proposes a fault-tolerant control scheme, establishing a kinematic model considering disturbances and failures, and adopts model predictive control for trajectory tracking. Additionally, an extended state observer is introduced to observe system states and counteract disturbances. To address potential failure issues, a controller reconstruction strategy is proposed. Finally, the effectiveness and superiority of the controller is validated through numerical simulation and comparative experiment. © 2024 IEEE.

关键词： Mobile robots

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Evolution of Cooperation in Snowdrift Game with Multi-Memory Mechanism 42

Evolution of Cooperation in Snowdrift Game with Multi-Memory...

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42nd Chinese control Conference, CCC 2023

作者： Liu, Yaojun Liu, Xingwen Tashi, Nyima College of Electrical Engineering Southwest Minzu University Lab. of Complex Systems & Intelligent Control Key Lab. of Electronic Information of State Ethnic Affairs Commission Sichuan Chengdu610225 China Engineering Research Center for Tibetan Information Processing School of Information Science and Technology Tibet University Lhasa850000 China

ISBN: (纸本)9789887581543

Cooperative behavior has been of great concern in evolutionary game researches because of its important role in social life and natural evolution. Since memory can greatly influence the emergence of cooperative behavior, memory-based research on evolutionary games has proliferated in recent years. In the present paper, inspired by the well-known 'Stanford marshmallow experiment' (SME), we proposed a multi-memory mechanism in Snowdrift game (SDG) on spatial lattice networks whose core lies in what follows: Players are divided into two groups according to individual self-control;different memory lengths are set by group and by time in a single realization. The simulation results show that our proposed mechanism promotes cooperation level of the considered evolutionary game. More specifically, as memory length increases to an intermediate length, the cooperation level increases as well. For mechanism with short memory length, the effect of population structure is obvious and small values of adjusting factor can intensively facilitate high-frequency cooperative behavior. These findings may be helpful to understand the connection between population heterogeneity and the emergence of high cooperation. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Behavioral research

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The DAO to Social Transportation: Towards Smart Mobility in Cyber-Physical-Social Space

The DAO to Social Transportation: Towards Smart Mobility in ...

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IEEE International Conference on systems, Man and Cybernetics

作者： Yuanyuan Chen Yisheng Lv Fei-Yue Wang State Key Lab. of Multimodal Artificial Intelligence Systems Chinese Academy of Sciences Institute of Automation Beijing China State Key Lab. for Management and Control of Complex Systems Chinese Academy of Sciences Beijing China

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