检索结果-内蒙古大学图书馆

Conditional generative adversarial network for segmentation and image reconstruction of grape berries in variable illumination conditions

引用

Expert Systems with Applications 2025年 287卷

作者： Navarro, Pedro J. Salas, Eduardo Rosique, Francisca Ruszczak, Bogdan Egea-Cortines, Marcos Campus Muralla del Mar s/n Universidad Politécnica de Cartagena Cartagena30202 Spain Faculty of Electrical Engineering Automatic Control and Informatics Department of Informatics Opole University of Technology Prószkowska 76 Opole45-758 Poland Genética Molecular Instituto de Biotecnología Vegetal Edificio I+D+I Plaza del Hospital s/n Universidad Politécnica de Cartagena Cartagena30202 Spain

One of the most significant challenges faced by computer vision algorithm developers is effectively handling images captured in variable illumination scenarios, which may include poorly lit environments, object occlusions, reflections, or even partial visibility. The introduction of deep learning techniques has marked an unprecedented advance in segmentation, identification, and object reconstruction in such environments. This research presents a deep learning architecture based on a Conditional Generative Adversarial Network (cGAN) specifically designed for various grape berry segmentation varieties under any illumination conditions. It exploits a dedicated data collection for training and testing the cGAN segmentation model, that consists of 25,350 images of five grape berry varieties, divided into two sets: 20,350 for training and 5,000 for testing. To evaluate the impact of convolution kernel sizes on the segmentation process within the GAN architecture, six models were trained using kernel sizes of 2x2, 4x4, 6x6, 8x8, 10x10, and 12x12. Five metrics (accuracy, precision, recall, F1-score, and IoU) were employed to facilitate comparison of result with similar segmentation methods. The metrics have been calculated on a dataset with images in variable illumination conditions and in five specific scenarios with images categorized as: (a) good illumination, (b) poor illumination;(c) lack of illumination;(d) noisy image and (e) noisy and poor illumination. Among all the assessed model configurations, the cGAN model with a convolution kernel size of 6x6 exhibited the best performance on the test set, achieving the following metrics: accuracy of 0.9970, precision of 0.9862, recall of 1.0000, F1-score of 0.9930, and IoU of 0.9813. Notably, when compared to other similar grape segmentation studies, the Pix2Pix architecture utilized in this work consistently delivered the best results across all the evaluated metrics. Furthermore, the proposed architecture is able to recon

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Numerical Simulation of 3D Printed Resin Droplet-Based Microfluidic Device With T-Junction Geometry

Numerical Simulation of 3D Printed Resin Droplet-Based Micro...

引用

International Conference on Instrumentation control and Automation (ICA)

作者： Febricetta Zahraketzia Sarwono Muhammad Azhar Fa’iq Isa Anshori Narendra Kurnia Putra Engineering Physics Department Faculty of Industrial Technology Institut Teknologi Bandung Bandung Indonesia Biomedical Engineering Department School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Instrumentation and Control Research Group Faculty of Industrial Technology Institut Teknologi Bandung Bandung Indonesia

Droplet-based microfluidics is a device that can process fluids on a micro-scale to be broken down into uniform droplets at a relatively fast rate. The droplet forming process can be done in a T-junction droplet-based microfluidics configuration where a dispersed fluid is injected into a continuous fluid flow to produce dispersed fluid droplets. In general, droplet-based microfluidics research is done using experimental tests which are limited in empirical observation, especially for mass production cases where an optimized design is needed. In this study, a numerical simulation was carried out to replicate the droplet generation in the droplet-based microfluidic device based on three-dimensional (3D) printed resin T-junction geometric scheme. Numerical simulation was carried out in a two-dimensional (2D) simulation using the level-set method (LSM) based on the finite element method (FEM) using computational fluid dynamics (CFD) tools for two-phase flow. Water is used as the dispersed fluid, and silicone oil 350 cp is used as the continuous fluid streamed into microfluidic channels with a height of 0.5 mm and a flow rate of 2.5 ml/hr. This study provides the influence of physical parameters such as the shear stress, pressure, and velocity profile which are evaluated at an evaluation point which directly affects the formation of droplets due to the interaction between two immiscible fluids. In addition, suggestions for future droplet generation simulations in microfluidics simulations are also obtained.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Neural network developed for obstacle avoidance of the four wheeled electric vehicle

Neural network developed for obstacle avoidance of the four ...

引用

IEEE International Conference on Electronics, Circuits and Systems (ICECS)

作者： Grazia Lo Sciuto Paweł Kowol Paweł Nowak Wacław Banás Salvo Coco Giacomo Capizzi Department of Mechatronics Silesian University of Technology Gliwice Poland Department of Electrical Electronics and Informatics Engineering University of Catania Catania Italy Department of Automatic Control and Robotic Silesian University of Technology Gliwice Poland Department of Mathematics Applications and Methods for Artificial Intelligence Faculty of Applied Mathematics Silesian University of Technology Gliwice Poland

Several solutions have been proposed for vehicle navigation in unknown environments to ensure safer driving by avoiding obstacles and collisions. In this work, an electric vehicle equipped with Mecanum 4 omnidirectional holonomic wheels, analog joystick to control driving movement, LiDAR sensors and Wi-Fi able to detect obstacles is investigated based on neural network approach. By experimental tests conducted to avoid collisions by detecting the presence of obstacles, the relation between the resistance distance and speed is described by the artificial neural network.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Optimizing Indoor Vertical Farming with DDPG Reinforcement Learning: Enhancing control of Nutrient Levels, Climate Conditions, and Plant Health

Optimizing Indoor Vertical Farming with DDPG Reinforcement L...

引用

International Conference on Technology, informatics, Management, engineering, and Environment (TIME-E)

作者： Albert Good Fried Panggabean Rahmat Romadhon Ramot Lubis Endra Joelianto Doctoral Program in Engineering Physics Institut Teknologi Bandung Bandung Indonesia Faculty of Informatics and Electrical Engineering Institut Teknologi Del Toba Indonesia Engineering Physics Study Program Institut Teknologi Bandung Bandung Indonesia Instrumentation Control and Automation Research Group Institut Teknologi Bandung Bandung Indonesia

ISBN: (数字)9798350364750

ISBN: (纸本)9798350364767

In indoor vertical farming systems, managing dynamic and complex environments poses significant challenges. Traditional control strategies often fall short in adapting to rapid changes in critical parameters such as nutrient levels, climate conditions, and plant health indicators. To address these challenges, this paper presents a novel approach for optimizing indoor vertical farming using Deep Deterministic Policy Gradient (DDPG), a reinforcement learning algorithm well-suited for environments with continuous action spaces. Our study focused on the control and monitoring of key parameters, including nutrient levels (pH and EC), climate conditions (temperature, humidity, light, and CO2 levels), and plant health indicators (biomass accumulation and leaf size structure). By defining a comprehensive state and action space, we simulated an indoor farming environment and trained the DDPG model to maximize crop yield and health.

关键词： Smart agriculture Precision agriculture Reinforcement learning Humidity Aerospace electronics Nutrients Temperature control informatics Monitoring Farming

来源：评论

学校读者我要写书评

暂无评论

Improving fNIRS Signal Quality Using Smoothing Filtering

Improving fNIRS Signal Quality Using Smoothing Filtering

引用

Progress in Applied electrical engineering (PAEE)

作者： Aleksandra Kawala-Sterniuk Dariusz Mikołajewski Luis A. Leiva Tuukka Ruotsalo Adam Lysiak Barbara Grochowicz Edward Jacek Gorzeńariczyk Adrian Luckiewicz Anna Wieczorek Mariusz Pelc Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland Institute of Computer Science Kazimierz Wielki University Bydgoszcz Poland Department of Computer Science University of Luxembourg Luxembourg Luxembourg University of Helsinki Denmark University of Copenhagen Finland Institute of Philosophy Kazimiez Wielki University Bydgoszcz Poland

Biomedical signals are extremely difficult to analyze, mainly due to the non-stationary nature of these signals. Filtering does not always bring the desired results, because often the desired information is filtered out. In the case of EEG signals, smoothing filters gave very good results. In this paper, various types of smoothing filters for the analysis of infrared spectroscopy signals were compared.

关键词：

来源：评论

学校读者我要写书评

暂无评论

DAFNI: A computational platform to support infrastructure systems research

引用

Proceedings of the Institution of Civil Engineers: Smart Infrastructure and Construction 2023年第3期176卷 108-116页

作者： Matthews, Brian Hall, Jim Batty, Michael Blainey, Simon Cassidy, Nigel Choudhary, Ruchi Coca, Daniel Hallett, Stephen Harou, Julien J James, Phil Lomax, Nik Oliver, Peter Sivakumar, Aruna Tryfonas, Theodoros Varga, Liz Scientific Computing Department Science and Technology Facilities Council Didcot United Kingdom School of Geography and the Environment University of Oxford Oxford United Kingdom Centre for Advanced Spatial Analysis University College London London United Kingdom Transportation Research Group Faculty of Engineering and Physical Sciences University of Southampton Southampton United Kingdom Department of Civil Engineering University of Birmingham Birmingham United Kingdom Department of Engineering University of Cambridge Cambridge United Kingdom Department of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom Centre for Environmental and Agricultural Informatics Cranfield University Cranfield United Kingdom Department of Mechanical Aerospace and Civil Engineering University of Manchester Manchester United Kingdom School of Engineering Newcastle University Newcastle United Kingdom School of Geography University of Leeds Leeds United Kingdom Department of Civil and Environmental Engineering Imperial College London London United Kingdom Department of Civil Engineering University of Bristol Bristol United Kingdom Department of Civil Environmental and Geomatic Engineering University College London London United Kingdom

Research into the engineering of infrastructure systems is increasingly data intensive. Researchers build computational models to explore scenarios such as investigating the merits of infrastructure plans, analysing historical data to inform system operations or assessing the impacts of infrastructure on the environment. Models are more complex, at higher resolution and with larger coverage. Researchers also require a 'multi-systems' approach to explore interactions between systems, such as energy and water with urban development, and across scales, from buildings and streets to regions or nations. Consequently, researchers need enhanced computational resources to support cross-institutional collaboration and sharing at scale. The Data and Analytics Facility for National Infrastructure (DAFNI) is an emerging computational platform for infrastructure systems research. It provides high-throughput compute resources so larger data sets can be used, with a data repository to upload data and share these with collaborators. Users' models can also be uploaded and executed using modern containerisation techniques, giving platform independence, scaling and sharing. Further, models can be combined into workflows, supporting multi-systems modelling and generating visualisations to present results. DAFNI forms a central resource accessible to all infrastructure systems researchers in the UK, supporting collaboration and providing a legacy, keeping data and models available beyond the lifetime of a project. © 2023 Emerald Publishing Limited: All rights reserved.

关键词： Urban growth

来源：评论

学校读者我要写书评

暂无评论

Grey Wolf Optimization Based Tuning of Terminal Sliding Mode controllers for a Quadrotor

引用

Computers, Materials & Continua 2021年第8期68卷 2265-2282页

作者： Rabii Fessi Hegazy Rezk Soufiene Bouallègue Research Laboratory in Automatic Control(LARA) National Engineering School of Tunis(ENIT)University of Tunis EL MANARTunis1002Tunisia College of Engineering at Wadi Addawaser Prince Sattam Bin Abdulaziz UniversityAl-Kharj11911Saudi Arabia Department of Electrical Engineering Faculty of EngineeringMinia UniversityMinia61517Egypt High Institute of Industrial Systems of Gabès(ISSIG) University of GabèsGabès6011Tunisia

The research on Unmanned Aerial Vehicles(UAV)has intensified considerably thanks to the recent growth in the fields of advanced automatic control,artificial intelligence,and *** this paper,a Grey Wolf Optimization(GWO)algorithm is proposed and successfully applied to tune all effective parameters of Fast Terminal Sliding Mode(FTSM)controllers for a quadrotor UAV.A full control scheme is first established to deal with the coupled and underactuated dynamics of the *** for altitude,attitude,and position dynamics become separately designed and *** work around the repetitive and time-consuming trial-error-based procedures,all FTSM controllers’parameters for only altitude and attitude dynamics are systematically tuned thanks to the proposed GWO *** a hard and complex tuning task is formulated as a nonlinear optimization problem under operational *** performance and robustness of the GWO-based control strategy are compared to those based on homologous metaheuristics and standard terminal sliding mode *** simulations are carried out to show the effectiveness and superiority of the proposed GWO-tuned FTSM controllers for the altitude and attitude dynamics’stabilization and *** statistical analyses revealed that the GWO algorithm is more competitive with high performance in terms of fastness,non-premature convergence,and research exploration/exploitation capabilities.

关键词： Quadrotor cascade control fast terminal sliding mode control grey wolf optimizer nonparametric Friedman analysis

来源：评论

学校读者我要写书评

暂无评论

The applied principles of EEG analysis methods in neuroscience and clinical neurology

引用

Military Medical Research 2024年第6期11卷 907-941页

作者： Hao Zhang Qing-Qi Zhou He Chen Xiao-Qing Hu Wei-Guang Li Yang Bai Jun-Xia Han Yao Wang Zhen-Hu Liang Dan Chen Feng-Yu Cong Jia-Qing Yan Xiao-Li Li School of Systems Science Beijing Normal UniversityBeijing 100875China College of Electrical and Control Engineering North China University of TechnologyBeijing 100041China School of Automation Science and Engineering South China University of TechnologyGuangzhou 510641China Department of Psychology the State Key Laboratory of Brain and Cognitive Sciencesthe University of Hong KongHong Kong SAR 999077China HKU-Shenzhen Institute of Research and Innovation Shenzhen 518057GuangdongChina Department of Health Technology and Informatics the Hong Kong Polytechnic UniversityHong Kong SAR 999077China Department of Rehabilitation Medicine the First Afliated Hospital of Nanchang UniversityNanchang 330006China Rehabilitation Medicine Clinical Research Center of Jiangxi Province Nanchang 330006China Beijing Key Laboratory of Learning and Cognition School of PsychologyCapital Normal UniversityBeijing 100048China School of Communication Science Beijing Language and Culture UniversityBeijing 100083China Institute of Electrical Engineering Yanshan UniversityQinhuangdao 066004HebeiChina School of Computer Science Wuhan UniversityWuhan 430072China School of Biomedical Engineering Faculty of Electronic Information and Electrical EngineeringDalian University of TechnologyDalian 116081LiaoningChina Guangdong Artifcial Intelligence and Digital Economy Laboratory(Guangzhou) Guangzhou 510335China.

Electroencephalography(EEG)is a non-invasive measurement method for brain *** to its safety,high resolution,and hypersensitivity to dynamic changes in brain neural signals,EEG has aroused much interest in scientific research and medical *** article reviews the types of EEG signals,multiple EEG signal analysis methods,and the application of relevant methods in the neuroscience feld and for diagnosing neurological ***,3 types of EEG signals,including time-invariant EEG,accurate event-related EEG,and random event-related EEG,are ***,5 main directions for the methods of EEG analysis,including power spectrum analysis,time-frequency analysis,connectivity analysis,source localization methods,and machine learning methods,are described in the main section,along with diferent sub-methods and effect evaluations for solving the same ***,the application scenarios of different EEG analysis methods are emphasized,and the advantages and disadvantages of similar methods are *** article is expected to assist researchers in selecting suitable EEG analysis methods based on their research objectives,provide references for subsequent research,and summarize current issues and prospects for the future.

关键词： Electroencephalogram analysis methods Applied principles Neuroscience Diagnosis Neurological diseases

来源：评论

学校读者我要写书评

暂无评论

Resilient Routing Table Computation Based on Connectivity Preserving Graph Sequences

Resilient Routing Table Computation Based on Connectivity Pr...

引用

IEEE Annual Joint Conference: INFOCOM, IEEE Computer and Communications Societies

作者： János Tapolcai Péter Babarczi Pin-Han Ho Lajos Rónyai Department of Telecommunications and Media Informatics Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Budapest Hungary Deptartment of Electrical and Computer Engineering University of Waterloo Canada Eötvös Loránd Research Network and Department of Algebra Institute for Computer Science and Control Institute of Mathematics Budapest University of Technology and Economics Budapest Hungary

Fast reroute (FRR) mechanisms that can instantly handle network failures in the data plane are gaining attention in packet-switched networks. In FRR no notification messages are required as the nodes adjacent to the failure are prepared with a routing table such that the packets are re-routed only based on local information. However, designing the routing algorithm for FRR is challenging because the number of possible sets of failed network links and nodes can be extremely high, while the algorithm should keep track of which nodes are aware of the failure. In this paper, we propose a generic algorithmic framework that combines the benefits of Integer Linear Programming (ILP) and an effective approach from graph theory related to constructive graph characterization of k-connected graphs, i.e., edge splitting-off. We illustrate these benefits through arborescence design for FRR and show that (i) due to the ILP we have great flexibility in defining the routing problem, while (ii) the problem can still be solved very fast. We demonstrate through simulations that our framework outperforms state-of-the-art FRR mechanisms and provides better resilience with shorter paths in the arborescences.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Modeling the Correlation of Human Vertebral Body Volumes*

引用

IFAC-PapersOnLine 2023年第2期56卷 9030-9035页

作者： Bálint Szabó Ákos Szlávecz Sándor Bazsó Péter Somogyi Katalin Kovács Árpád Viola Balázs István Benyó Budapest University of Technology and Economics Faculty of Electrical Engineering and Information Technology Department of Control Engineering and Information Technology Budapest Hungary. Department of Informatics Széchenyi István University Győr Hungary Péterfy Sándor Street Hospital Department of Neurosurgery Budapest Hungary

Anatomical parameters of the human body strongly correlate with each other. Modelling these dependencies enables the creation of a realistic anatomical human body model that can be parameterized. Such a model can be used for several diagnostic processes to identify abnormalities or even give guidance in surgical interventions. This paper proposes a probabilistic model describing the dependencies between the vertebral body volumes of humans from the Caucasian human race. As demonstrated, the proposed model can accurately describe the relationship between the vertebral body volumes and is used for the prediction of an unknown vertebral volume based on a known one. The probabilistic model is created by using the CT segmentation of 37 patients.

关键词： Biomedical engineering Statistical Modelling Human Body Modelling Spinal Chord Segmentation Probabilistic Model

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：