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SE-COTR: A Novel Fruit Segmentation Model for Green Apples Application in Complex Orchard

Plant Phenomics 2022年第1期4卷 12-25页

作者： Zhifen Wang Zhonghua Zhang Yuqi Lu Rong Luo Yi Niu Xinbo Yang Shaoxue Jing Chengzhi Ruan Yuanjie Zheng Weikuan Jia School of Information Science and Engineering Shandong Normal UniversityJinan 250358China State Key Laboratory of Biobased Materials and Green Papermaking Qilu University of Technology(Shandong Academy of Science)Jinan 25035China School of Informatics University of LeicesterLeicester LE17RHUK Department of Engineering Design and Mathematics University of the West of EnglandBristol BS161QYUK Fujian Key Laboratory of Intelligent Control and Manufacturing of Agricultural Machinery Wuyishan 354300China Key Laboratory of Facility Agriculture Measurement and Control Technology and Equipment of Machinery Industry Jiangsu UniversityZhenjiang 212013China

Because of the unstructured characteristics of natural orchards,the efficient detection and segmentation applications of green fruits remain an essential challenge for intelligent ***,an innovative fruit segmentation method based on deep learning,termed SE-COTR(segmentation based on coordinate transformer),is proposed to achieve accurate and real-time segmentation of green apples.

关键词： Application segmentation Complex

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Structural damage mitigation using a fuzzy controller 23

Structural damage mitigation using a fuzzy controller

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23rd International Conference on control Systems and Computer Science Technologies, CSCS 2021

作者： Munteanu, Ruben Iacob Stamatescu, Iulia Calofir, Vasile Nica, George Bogdan Iliescu, Sergiu Stelian Politehnica University of Bucharest Department of Automatic Control and Industrial Informatics Bucharest Romania Technical University of Civil Engineering Department of Mechanics of Structures Bucharest Romania

ISBN: (纸本)9781665439398

Seismic design of buildings for elastic behavior is a major challenge in civil engineering field. The economic requirements imply that in general the structural elements dissipate earthquake induced energy through plastic deformations. This means that certain level of structural damage must be accepted. The main objective of this paper is the mitigation of seismic structural response, using a fuzzy controller, with the aim to maintain an elastic behavior throughout an entire seismic event. In this regard, a finite element plane frame model was constructed and simulated using the Force Analogy Method together with the State Space formulation. Furthermore, a comparative analysis of the structural response with and without control implementation was carried out. The results illustrate the efficiency of the fuzzy controller. © 2021 IEEE.

关键词： Simulink

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Expression recognition based on convolutional difference contextual feature fusion

Expression recognition based on convolutional difference con...

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2022 International Conference on Electronic Information engineering and Computer Science, EIECS 2022

作者： Lu, Shengfu Yang, Chuang Li, Mi Kang, Jiaming Faculty of Information Technology Beijing University of Technology Beijing International Collaboration Base on Brain Informatics and Wisdom Services Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing China Department of Automation Faculty of Information Technology Beijing University of Technology Beijing China Department of Automation Faculty of Information Technology Beijing China

ISBN: (纸本)9781510663312

Facial expression recognition has always been a focus of study in emotion computing. With the aim of solving the problem that previous facial expression recognition studies are susceptible to individual differences and background noise, as well as the loss of facial expression features in deep networks of deep convolutional networks, we propose a facial expression method based on convolutional difference contextual feature fusion. The convolutional difference module can carry out difference operation between emotional image and neutral image in the input image, eliminate individual difference and background noise in expression features and improve the accuracy and generalization of the network. Finally, convolutional difference and contextual features are combined to improve the accuracy of the network further. Experiment results of 4 public facial expression datasets illustrate that compared with the existing facial expression recognition methods, this method has higher accuracy, can extract facial expression features more effectively, and has a better generalization ability. © 2023 SPIE.

关键词： Convolutional neural networks

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Accelerating Stable Matching between Workers and Spatial-Temporal Tasks for Dynamic MCS: A Stagewise Service Trading Approach

arXiv

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arXiv 2025年

作者： Qi, Houyi Liwang, Minghui Wang, Xianbin Fu, Liqun Hong, Yiguang Li, Li Cheng, Zhipeng School of Informatics Xiamen University Fujian China Department of Control Science and Engineering Canada Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China Department of Electrical and Computer Engineering Western University ON Canada School of Future Science and Engineering Soochow University Jiangsu China

Designing proper incentives in mobile crowdsensing (MCS) networks represents a critical mechanism in engaging distributed mobile users (workers) to contribute heterogeneous data for diverse applications (tasks). We develop a novel stagewise trading framework to reach efficient and stable matching between tasks and workers, upon considering the diversity of tasks and the dynamism of MCS networks. This framework integrates futures and spot trading stages, where in the former, we propose futures trading-driven stable matching and pre-path-planning (FT-SMP3) for long-term task-worker assignment and pre-planning of workers’ paths based on historical statistics and risk analysis. While in the latter, we investigate spot trading-driven DQN path planning and onsite worker recruitment (ST-DP2WR) mechanism to enhance workers’ and tasks’ practical utilities by facilitating temporary worker recruitment. We prove that our proposed mechanisms support crucial properties such as stability, individual rationality, competitive equilibrium, and weak Pareto optimality theoretically. Also, comprehensive evaluations confirm the satisfaction of these properties in practical network settings, demonstrating our commendable performance in terms of service quality, running time, and decision-making overheads. Copyright © 2025, The Authors. All rights reserved.

关键词： Risk analysis

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Assessment of Depression Level Based on Multi-Scale 3D Convolution and Expression Videos 3

Assessment of Depression Level Based on Multi-Scale 3D Convo...

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3rd International Conference on Computer Vision and Pattern Analysis, ICCPA 2023

作者： Cao, Qishuang Gao, Junlong Lv, Zeying Li, Mi Department of Automation Faculty of Information Technology Beijing University of Technology Beijing100124 China Beijing International Collaboration Base on Brain Informatics and Wisdom Services Beijing100124 China Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing100124 China Engineering Research Center of Digital Community Ministry of Education Beijing100124 China

ISBN: (纸本)9781510667563

The automatic diagnosis of depression using deep learning has recently shown significant progress, and 3DCNN has been applied to assessing depression levels from videos. There are two problems to be encountered applying 3DCNN, including insufficient data to train the model and an insufficient diversity of features extracted on a single scale. An approach is presented in this paper to address these issues. Firstly, we augmented the raw data by adding noise and applying rotations to increase the amount of the training set. Secondly, we constructed a 3DCNN to extract more diverse features from multiscales. We evaluated our proposed method on the AVEC 2014. Our approach achieved MAE=7.13 and RMSE=9.16, demonstrating its effectiveness in improving the accuracy of depression assessment compared to existing approaches. © 2023 SPIE.

关键词： Deep learning

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QuITO v.2: Trajectory Optimization with Uniform Error Guarantees under Path Constraints

arXiv

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arXiv 2024年

作者： Ganguly, Siddhartha D’Silva, Rihan Aaron Chatterjee, Debasish Systems and Control Engineering Indian Institute of Technology Mumbai400076 India Applied Mathematics and Physics Graduate School of Informatics Kyoto University Japan Department of Aerospace Engineering University of Illinois at Urbana-Champaign United States

This article introduces a new transcription, change point localization, and mesh refinement scheme for direct optimization-based solutions and for uniform approximation of optimal control trajectories associated with a class of nonlinear constrained optimal control problems (OCPs). The base transcription algorithm for which we establish the refinement algorithm is a direct multiple shooting technique — QuITO v.2 (Quasi-Interpolation based Trajectory Optimization). The mesh refinement technique consists of two steps — localization of certain irregular regions in an optimal control trajectory via wavelets, followed by a targeted ℎ-refinement approach around such regions of irregularity. Theoretical approximation guarantees on uniform grids are presented for optimal controls with certain regularity properties along with guarantees of localization of change points by wavelet transform. Numerical illustrations are provided for control profiles involving discontinuities to show the effectiveness of the localization and refinement strategy. We also announce, and make freely available, a new software package based on QuITO v.2 along with all its functionalities for completeness. The package is available at: https://***/chatterjee-d/***. Copyright © 2024, The Authors. All rights reserved.

关键词： Mesh generation

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Advancement of Circular Economy Supported by Intelligent Communication System 4th

Advancement of Circular Economy Supported by Intelligent Com...

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4th International Conference on Sustainable Energy for Smart Cities, SESC 2022

作者： Behúnová, Annamária Knapčíková, Lucia Martiček, Matúš Faculty of Mining Ecology Process Control and Geotechnologies Institute of Earth Resources Technical University of Košice Prešov Slovakia Faculty of Manufacturing Technologies With a Seat in Prešov Department of Industrial Engineering and Informatics The Technical University of Košice Bayerova 1 Prešov080 01 Slovakia

ISBN: (纸本)9783031339783

However, the linear economy and its current model will not be able to ensure long-term sustainability. It is not appropriate, and above all possible, to increase production from primary sources indefinitely. In some areas, it directly affects the population's life. It brings negative elements, such as climate change, increasing differences between poor and rich regions, and natural disasters with more serious consequences. Emerging problems such as the deterioration of air, soil and water quality directly impact declining human well-being. But there is an economic model in which such non-ecological behaviour and waste of resources do not occur. This model is called a circular economy. The manuscript is focused on applying the circular economy within the enterprises of the Slovak Republic and individual EU states. An important task will be to use the information system and the method for obtaining data and subsequent processing. A properly set up circular economy can minimize the waste of resources, improve the efficiency of their use, reduce g reenhouse gas emissions and contribute to the preservation of biodiversity. © 2023, ICST Institute for Computer Sciences, Social informatics and Telecommunications engineering.

关键词： Sustainable development

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Prediction of Risks Assessment in the Workplace Using Online Monitoring 4th

Prediction of Risks Assessment in the Workplace Using Online...

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4th International Conference on Sustainable Energy for Smart Cities, SESC 2022

作者： Knapčíková, Lucia Behúnová, Annamária Husár, Jozef Tauberová, Rebeka Martiček, Matúš Faculty of Manufacturing Technologies With a Seat in Prešov Department of Industrial Engineering and Informatics The Technical University of Košice Bayerova 1 Prešov080 01 Slovakia Faculty of Mining Ecology Process Control and Geotechnologies Institute of Earth Resources Technical University of Košice Košice Slovakia

ISBN: (纸本)9783031339783

The digitization of technological processes in enterprises is rapidly changing the world of work and requires new and up-to-date solutions in occupational health and safety (OSH). The European Agency for Safety and Health at Work (EU-OSHA) provide information to policymakers, researchers and workers about the possible effects of digitization on OSH, so that they can take timely and effective measures to ensure the safety and protection of workers. Occupational health and safety are often poorly managed in micro and small enterprises, and employees are exposed to a greater risk of workplace injuries and occupational diseases. The paper deals with online monitoring of risk assessment in the injection moulding workplace and is key to creating healthy workplaces. However, conducting a risk assessment can be quite challenging, especially for micro and small businesses that may lack the resources or expertise to do it effectively. © 2023, ICST Institute for Computer Sciences, Social informatics and Telecommunications engineering.

关键词： Risk assessment

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Automated Depression Diagnosis Based on Facial Expression and Deep Dual-Stream Convolutional Neural Networks 3

Automated Depression Diagnosis Based on Facial Expression an...

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3rd International Conference on Computer Vision and Pattern Analysis, ICCPA 2023

作者： Chen, Yangyang Chen, Yingyu Li, Mi Department of Automation Faculty of Information Technology Beijing University of Technology Beijing100124 China Beijing International Collaboration Base on Brain Informatics and Wisdom Services Beijing100124 China Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing100124 China Engineering Research Center of Digital Community Ministry of Education Beijing100124 China

ISBN: (纸本)9781510667563

Depression is a common mental illness characterized by symptoms such as low mood, pessimism, and insomnia. In this study, we developed a deep Dual-Stream CNN to automatically diagnose and classify depression in expression video sequences. The network has two branches that extract static features and dynamic features from static and dynamic expressions, respectively, which are then fused for depression classification. The experiments were performed on the AVEC2014 database, and the results showed that the Dual-Stream model significantly improved the classification performance of depression, achieving an accuracy of 69.08% in depression categorization. © 2023 SPIE.

关键词： Convolutional neural networks

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Ontological Decision Support Model for Cargo Port Risk Management

Ontological Decision Support Model for Cargo Port Risk Manag...

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Information, control, and Communication Technologies (ICCT), International Conference on

作者： Irina Bondareva Oleg Protalinskiy Anna Khanova Evgeniya Nesterova Anastasiya Belova Department of Applied informatics Astrakhan State Technical University Astrakhan Russia Department of Automated control systems of thermal processes Moscow Power Engineering Institute Moscow Russia

Modern unstable conditions of the market environment dictate the need for transport logistics enterprises to predict possible risk situations in order to prevent them, as well as to develop tools that allow forming management decisions, evaluating the effectiveness of each of them and choosing the most appropriate one, taking into account specific tasks and various influencing factors. As risks, situations of failure to achieve the goals of the cargo port, as well as failure to achieve standard values by the indicators for assessing these goals are considered. Goals and indicators are indicated in the constructed balanced scorecard (BSC). A set of links between goals and indicators for their assessment with risks at various levels of management is presented in the form of a developed multi-level hybrid logical-probabilistic (LP) risk model of the cargo port, as well as in detailed scenario models of this LP model. The ontological model contains all the information about the interaction of elements that affect the onset of risky events, and allows you to select options for exiting a risky situation in accordance with various specified conditions. The simulation model allows, based on the results of requests to the ontological model and the scenarios of simulation experiments developed on their basis, to develop a management decision that allows avoiding risky situations in the longer term, taking into account all available stochastic characteristics and factors of influence.

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