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检索条件"任意字段=Proceedings of the 3rd International Conference on Control and Computer Vision"

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Combining Gesture and Voice control for Mid-air Manipulation of CAD Models in VR Environments 16

Combining Gesture and Voice Control for Mid-air Manipulation...

引用

16th international Joint conference on computer vision, Imaging and computer Graphics Theory and Applications (VISIGRAPP) / 5th international conference on Human computer Interaction Theory and Applications (HUCAPP)

作者： Friedrich, Markus Langer, Stefan Frey, Fabian Ludwig Maximilians Univ Munchen Inst Informat Oettingenstr 67 D-80538 Munich Germany

ISBN: (纸本)9789897584886

Modeling 3D objects in domains like computer Aided Design (CAD) is time-consuming and comes with a steep learning curve needed to master the design process as well as tool complexities. In order to simplify the modeling process, we designed and implemented a prototypical system that leverages the strengths of Virtual Reality (VR) hand gesture recognition in combination with the expressiveness of a voice-based interface for the task of 3D modeling. Furthermore, we use the Constructive Solid Geometry (CSG) tree representation for 3D models within the VR environment to let the user manipulate objects from the ground up, giving an intuitive understanding of how the underlying basic shapes connect. The system uses standard mid-air 3D object manipulation techniques and adds a set of voice commands to help mitigate the deficiencies of current hand gesture recognition techniques. A user study was conducted to evaluate the proposed prototype. The combination of our hybrid input paradigm shows to be a promising step towards easier to use CAD modeling.

关键词： CAD Modeling Virtual Reality Speech Recognition Constructive Solid Geometry

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Automated Crop Growth Monitoring and Optimizing the Yield with Reinforcement Learning

Automated Crop Growth Monitoring and Optimizing the Yield wi...

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Mobile Networks and Wireless Communications (ICMNWC), IEEE international conference on

作者： Snehitha Gorantla S. Veluchamy Department of Computer Science and Engineering - Artificial Intelligence Amrita School of Computing Amrita Vishwa Vidyapeetham Chennai India Department of Computer Science and Engineering - Cyber Security Amrita School of Computing Amrita Vishwa Vidyapeetham Chennai India

A reinforcement learning agent for optimal green-house management through Proximal Policy Optimisation is developed and evaluated in this work. With variable elements like lighting, irrigation, humidity, and temperature, a virtual greenhouse is produced. By interacting with the surroundings, the agent modifies the controls and gets input on things like crop health and growth rate. For policy and value estimation, the neural network design consists of distinct actor and critic networks as well as shared feature layers. Compared to fixed or random policies, the trained agent shows the ability to regulate conditions for increased crop yield and sustainability. As the number of trials increased, the RL agent's average return per trial increased steadily. This suggests that the RL agent has become more adept at controlling the greenhouse environment in subsequent experiments. This demonstrates how well the RL agent can manage crop health and resource use in the greenhouse climate control system.

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Backstepping control of Air-Handling Unit for Indoor Temperature Regulation 1

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3rd international conference on Neural Computing for Advanced Applications, NCAA 2022

作者： Shang, Fang Ji, Yongshuai Duan, Jingdong Li, Chengdong Peng, Wei Shandong Key Laboratory of Intelligent Buildings Technology School of Information and Electrical Engineering Shandong Jianzhu University Jinan250101 China QingDao iESLab Electronic Co. LTD Jinan China

ISBN: (数字)9789811961427

ISBN: (纸本)9789811961410

The control of indoor temperature has significant importance to maintain excellent thermal comfort and energy saving. At present, indoor temperature is mainly controlled by Air-Handling Unit (AHU), so a proper indoor temperature control strategy plays an important role in temperature regulation. In this paper, we consider the temperature regulation of a room effected by solar radiation, floor temperature and walls temperature. The nonlinear dynamic model of the room is analyzed, and the state space representation is given. Then, by introducing suitable state transformation, a new system is obtained which is convenient for controller design. Subsequently, the controller is designed for the new system using backstepping technique, and the control objective is realized for indoor temperature regulation. Finally, numerical simulations are provided to illustrate the effectiveness of the backstepping controller, and comparisons are also given. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： controllers

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Research on Intelligent Energy Management of Fuel Cell Vehicle

Research on Intelligent Energy Management of Fuel Cell Vehic...

引用

Power Electronics, computer Applications (ICPECA), IEEE international conference on

作者： Tian Yang Songmao Wei Zilong Wang Jiashuai Li Peiliang Yu Department of Electrical & Electronic Control Development China Automotive Technology & Research Centre Co. Ltd Tianjin China

With the development of fuel cell technology, how to effectively reduce hydrogen consumption of fuel cell vehicles has become a technical focus and difficulty. This paper proposed an adaptive energy management algorithm which was suitable for fuel cell vehicles. First, the ECMS algorithm considering the durability of the fuel cell was established. In order to ensure the good performance of the ECMS algorithm, an equivalent factor optimization model was established, which adjusted the equivalent factor according to the changes of battery SOC and future velocity. Considering that in the actual driving environment, it was impossible to accurately obtain the upcoming driving velocity in the future. Therefore, it was hard to quickly adjust and select the equivalent factor. This article established a neural network velocity prediction model, and the predicted velocity were provided to the equivalent factor optimization model, and the adaptive energy management algorithm was accomplished. Simulation results showed that the adaptive algorithm reduced hydrogen consumption by 2.6% compared to the basic ECMS algorithm, while battery SOC was in a suitable wording window.

关键词： Adaptation models Hydrogen Predictive models Prediction algorithms Electromagnetic compatibility Fuel cell vehicles Batteries

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Improved Twin Network Target Tracking Algorithm Based on Hybrid Attention Mechanism

Improved Twin Network Target Tracking Algorithm Based on Hyb...

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Electronic Information Engineering and computer Science (EIECS), 2021 international conference on

作者： Xiaozheng Zhang Yuhang Pan Haili Zhao Department of Information and Control Technolog China Noeth Vehicle Research Insitute BeiJing China School of Electronic Information Engineering Changchun University of Science and Technology ChangChun China

Deep getting to know techniques are turning into extra and extra famous in the area of goal monitoring due to their effective function extraction capabilities, amongst which the twin network-based goal monitoring algorithm with excessive walking body price and robust monitoring fault tolerance has attracted the interest of many scholars. Aiming at the drawbacks that twin networks use an offline method to recognize end-to-end mannequin training, and the educated mannequin can't trade the community parameters and the goal template at some point of the monitoring process, this paper proposes an increased twin community goal monitoring algorithm primarily based on a hybrid interest mechanism, which is first off skilled offline on the education set of the ILSVRC2015 dataset, and then on the coaching units of ILSVRC2015 and The algorithm is examined and evaluated on a take a look at set on the plane class of the VOT2018 dataset, and the experimental outcomes exhibit that the success fee of the algorithm proposed in this paper is multiplied from 61.2% to 68.4% and the accuracy from 77.1% to 82.3% of the SiamFC base algorithm, which proves that the algorithm has properly monitoring performance.

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Learning Canonical View Representation for 3D Shape Recognition with Arbitrary Views 18

Learning Canonical View Representation for 3D Shape Recognit...

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18th IEEE/CVF international conference on computer vision (ICCV)

作者： Wei, Xin Gong, Yifei Wang, Fudong Sun, Xing Sun, Jian Xi An Jiao Tong Univ Xian Peoples R China Tencent Youtu Lab Shanghai Peoples R China

ISBN: (纸本)9781665428125

In this paper, we focus on recognizing 3D shapes from arbitrary views, i.e., arbitrary numbers and positions of viewpoints. It is a challenging and realistic setting for view-based 3D shape recognition. We propose a canonical view representation to tackle this challenge. We first transform the original features of arbitrary views to a fixed number of view features, dubbed canonical view representation, by aligning the arbitrary view features to a set of learnable reference view features using optimal transport. In this way, each 3D shape with arbitrary views is represented by a fixed number of canonical view features, which are further aggregated to generate a rich and robust 3D shape representation for shape recognition. We also propose a canonical view feature separation constraint to enforce that the view features in canonical view representation can be embedded into scattered points in a Euclidean space. Experiments on the ModelNet40, ScanObjectNN, and RGBD datasets show that our method achieves competitive results under the fixed viewpoint settings, and significantly outperforms the applicable methods under the arbitrary view setting.

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Improving the efficiency of software defined network through load balancing algorithms 3

Improving the efficiency of software defined network through...

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3rd international conference on Intelligent Communication Technologies and Virtual Mobile Networks, ICICV 2021

作者： Rukmini Bhat, B. Sneha, N.S. Bhat, Keerthana Kamath, Chaithra C. Naik, Chaitha Shri Madhwa Vadiraja Institute of Technology Management Department of Computer Science Udupi India

ISBN: (纸本)9780738111834

In this current era, usage of the internet is increasing drastically. Digitization has led to high network traffic which makes the overall management of network highly complex and expensive as traditional networks are non-programmable. As a solution for these issues in traditional networks, Software Defined Networking (SDN) has been introduced. SDN decouples the data plane and control plane, thereby making the network programmable. Load balancing in SDN is done to ensure effective management of resources as per client's request. This paper focuses on the effect of Load balancing on SDNs. Here, RTT is calculated for two cases. One, with application of least connection and Dijkstra algorithms and the other, without applying the algorithm. The result is compared to justify the efficiency improvement. We evaluate our system using mininet network emulator and the results demonstrate the feasibility and efficiency of our proposed scheme in terms of delay and overhead. © 2021 IEEE.

关键词： Software defined networking

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Water Life-Saving Robot Based on computer vision 23

Water Life-Saving Robot Based on Computer Vision

引用

proceedings of the 6th international conference on Information Technologies and Electrical Engineering

作者： Maoyuan Luo Urban Vocational College of Sichuan China

ISBN: (纸本)9798400708299

This project proposes an intelligent aquatic lifesaving robot based on computer vision and machine learning technology. The robot realizes high-precision positioning through multi-satellite positioning function, and is equipped with posture sensing function and computer vision function. It uses Convolutional neural network and Convolutional Pose Machine algorithm to realize human posture recognition. At the same time, the robot has the function of self-balance adjustment and wireless charging, which improves the stability and sustainability of the robot. The experimental results show that the effect of action recognition using 3D convolutional neural network is better than the traditional k-nearest neighbor classifier and support vector machine classifier. In the Weizmann action database, the recognition rate of 3D convolutional neural network reaches 96.3%, which is significantly higher than 90.6% of K-nearest classifier and 93.1% of support vector machine classifier. In the KTH action database, the recognition rate of 3D convolutional neural network is 90.3%, which is higher than 86.7% of K-nearest classifier and 89% of support vector machine classifier.

关键词： Aquatic intelligent life-saving robot action recognition computer vision convolutional neural network intelligent control system machine learning

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Design of a control System for Stabilizing the Angular Position of Platforms on a Movable Base

Design of a Control System for Stabilizing the Angular Posit...

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Informatics, Electronics, and Radio Engineering (PIERE), international conference Problems of

作者： Bui Van Tam Valery D. Yurkevich Missile and Gunnery Faculty Vietnam Naval Academy Nha Trang Vietnam Automation and Computer Engineering Faculty Novosibirsk State Technical University Novosibirsk Russia

ISBN: (数字)9798331516321

ISBN: (纸本)9798331516338

The problem of a control system design is discussed to provide an angular position platform stabilization. The platform is used to install various navigation equipment and communication devices. Stabilization of the platform's angular position eliminates the influence of vibrations of the platform's moving base on the operation of this equipment. The platform is equipped with an electrohydraulic drive, which ensures the horizontal position of the platform under conditions of vibrations of the vessel deck. The control system is designed in such a way that fast and slow processes are created in a closedloop system. The discussed approach to control system design allows to provide stability and robustness for position of the platform under vibrations of the vessel deck. The effect of the small parameters of the electrohydraulic drive on control system stability is treated. The selection of the controller parameters is carried out by additionally taking into account the sensitivity function, which reflects the influence of wave disturbances on the angular position of the platform.

关键词： Vibrations Sensitivity Navigation Design methodology Process control Drives control systems Robustness Electrohydraulics Informatics

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PSO Tuned Marine Microgrid Load Frequency control

PSO Tuned Marine Microgrid Load Frequency Control

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Electrical, computer, Communications and Mechatronics Engineering (ICECCME), international conference on

作者： Rajib Baran Roy Sanath Alahakoon Umme Mumtahina Ashfaque Ahmed Chowdhury School of Engineering and Technology Central Queensland University Gladstone Australia

This paper recommends a load frequency controller (LFC) for integrating non-conventional energy resources into marine vessel’s power system. The LFC, based on a conventional proportional integral derivative (PID) controller optimized using particle swarm optimization (PSO), addresses frequency deviations caused by non-conventional energy sources and non-linear dynamic loads in isolated hybrid marine microgrid. The controller's design considers transfer functions of microgrid components, while its performance is evaluated using integral time absolute error (ITAE) and integral time square error (ITSE) indices. Validation is conducted through real-time simulations using the DS 1104 R&D controller board. The operational results demonstrate the superior performance of the tuned LFC in regulating frequency deviations, with improved rise time, fall time, slew rate, and overshoot compared to the non-optimized controller. This research presents a resilient and efficient LFC design that effectively addresses frequency deviations in marine microgrids through the integration of non-conventional energy resources. The findings may contribute in advancing the sustainable operation of marine vessels, enabling energy source diversification and a reduction in greenhouse gas emissions.

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