检索结果-内蒙古大学图书馆

IEEE International Conference on Autonomous Robot systems and Competitions (ICARSC)

作者： Carlos A. Silva Sedat Dogru Lino Marques Department of Electrical and Computer Engineering Institute of Systems and Robotics University of Coimbra 3030-290 Coimbra Portugal

In order to guarantee a harmonious coexistence of robots and humans, it is vital for the former to be able to navigate the environment in a safe manner, taking into consideration the people that populate it. This requires the robot to be capable of identifying where the surrounding people are, through adequate processing of the sensory data acquired. In this paper we present a 3D person detection system for indoor settings which fuses RGB and LiDAR data, simultaneously using the semantic information available from the camera and the precise and long-range data acquired by the LiDAR. The proposed approach utilizes SVM with various feature vectors to classify the point clusters, and it also introduces planarity as another feature, improving the overall detection performance considerably.

关键词： Point cloud compression Support vector machines Laser radar Three-dimensional displays Navigation Robot vision systems Semantics

来源：评论

学校读者我要写书评

暂无评论

SPVSoAP3D: A Second-order Average Pooling Approach to enhance 3D Place Recognition in Horticultural Environments

arXiv

引用

arXiv 2024年

作者： Barros, T. Premebida, C. Aravecchia, S. Pradalier, C. Nunes, U.J. University of Coimbra Institute of Systems and Robotics Department of Electrical and Computer Engineering Portugal IRL2958 GeorgiaTechCNRS Metz57070 France

3D LiDAR-based place recognition has been extensively researched in urban environments, yet it remains underexplored in agricultural settings. Unlike urban contexts, horticultural environments, characterized by their permeability to laser beams, result in sparse and overlapping LiDAR scans with suboptimal geometries. This phenomenon leads to intra- and inter-row descriptor ambiguity. In this work, we address this challenge by introducing SPVSoAP3D, a novel modeling approach that combines a voxel-based feature extraction network with an aggregation technique based on a second-order average pooling operator, complemented by a descriptor enhancement stage. Furthermore, we augment the existing HORTO-3DLM dataset by introducing two new sequences derived from horticultural environments. We evaluate the performance of SPVSoAP3D against state-of-the-art (SOTA) models, including OverlapTransformer, PointNetVLAD, and LOGG3D-Net, utilizing a cross-validation protocol on both the newly introduced sequences and the existing HORTO-3DLM dataset. The findings indicate that the average operator is more suitable for horticultural environments compared to the max operator and other first-order pooling techniques. Additionally, the results highlight the improvements brought by the descriptor enhancement stage. The code is publicly available at https://***/Cybonic/*** © 2024, CC BY.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

SPVSoAP3D: A Second-order Average Pooling Approach to enhance 3D Place Recognition in Horticultural Environments

SPVSoAP3D: A Second-order Average Pooling Approach to enhanc...

引用

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

作者： T. Barros C. Premebida S. Aravecchia C. Pradalier U. J. Nunes Department of Electrical and Computer Engineering Institute of Systems and Robotics University of Coimbra Portugal IRL2958 GeorgiaTech-CNRS Metz France

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

3D LiDAR-based place recognition has been extensively researched in urban environments, yet it remains underexplored in agricultural settings. Unlike urban contexts, horticultural environments, characterized by their permeability to laser beams, result in sparse and overlapping LiDAR scans with suboptimal geometries. This phenomenon leads to intra-and inter-row descriptor ambiguity. In this work, we address this challenge by introducing SPVSoAP3D, a novel modeling approach that combines a voxel-based feature extraction network with an aggregation technique based on a second-order average pooling operator, complemented by a descriptor enhancement stage. Furthermore, we augment the existing HORTO-3DLM dataset by introducing two new sequences derived from horticultural environments. We evaluate the performance of SPVSoAP3D against state-of-the-art (SOTA) models, including OverlapTransformer, PointNetVLAD, and LOGG3D-Net, utilizing a cross-validation protocol on both the newly introduced sequences and the existing HORTO-3DLM dataset. The findings indicate that the average operator is more suitable for horticultural environments compared to the max operator and other first-order pooling techniques. Additionally, the results highlight the improvements brought by the descriptor enhancement stage. The code is publicly available at https://***/Cybonic/***

关键词： Solid modeling Three-dimensional displays Protocols Laser radar Urban areas Green products Laser modes Permeability Laser beams Intelligent robots

来源：评论

学校读者我要写书评

暂无评论

An Efficient Medical Image Deep Fusion Model Based on Convolutional Neural Networks

引用

computers, Materials & Continua 2023年第2期74卷 2905-2925页

作者： Walid El-Shafai Noha A.El-Hag Ahmed Sedik Ghada Elbanby Fathi E.Abd El-Samie Naglaa F.Soliman Hussah Nasser AlEisa Mohammed E.Abdel Samea Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Higher Institute of Commercial Science Management Information SystemsEl-Mahala El-KobraEgypt Department of the Robotics and Intelligent Machines Faculty of Artificial IntelligenceKafrelsheikh UniversityKafr El-SheikhEgypt Department of Industrial Electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia Medical Imaging and Interventional Radiology National Liver InstituteMenoufia UniversityEgypt

Medical image fusion is considered the best method for obtaining one image with rich details for efficient medical diagnosis and *** learning provides a high performance for several medical image analysis *** paper proposes a deep learning model for the medical image fusion *** model depends on Convolutional Neural Network(CNN).The basic idea of the proposed model is to extract features from both CT and MR ***,an additional process is executed on the extracted *** that,the fused feature map is reconstructed to obtain the resulting fused ***,the quality of the resulting fused image is enhanced by various enhancement techniques such as Histogram Matching(HM),Histogram Equalization(HE),fuzzy technique,fuzzy type,and Contrast Limited Histogram Equalization(CLAHE).The performance of the proposed fusion-based CNN model is measured by various metrics of the fusion and enhancement *** realistic datasets of different modalities and diseases are tested and ***,real datasets are tested in the simulation analysis.

关键词： Image fusion CNN deep learning feature extraction evaluation metrics medical diagnosis

来源：评论

学校读者我要写书评

暂无评论

Modular Cyber-Physical System for Smart Industry: A case study on energy load disaggregation

Modular Cyber-Physical System for Smart Industry: A case stu...

引用

2023 International Conference on Control, Automation and Diagnosis, ICCAD 2023

作者： Alves, Jorge Sousa, Pedro Matos, Barbara Mendes, Jerome Souza, Francisco Matias, Tiago University of Coimbra Institute of Systems and Robotics Department of Electrical and Computer Engineering Coimbra3030-290 Portugal Oncontrol Technologies Coimbra3000-108 Portugal Radboud University Dept. Analytical Chemistry & Chemometrics AJ Nijmegen6525 Netherlands

ISBN: (纸本)9798350347074

Constant changes have marked the industry, and cyber-physical systems have offered great potential in Industry 4.0 on production processes, allowing the integration of computational intelligence and real-time processing. In this context, this paper proposes a modular hardware system for industrial applications according to a plug & play concept. The proposed system comprises a processing module (mPP) and specific expansion modules (mEXs). The mPP is responsible for administrating the network/communication. It collects data from the mEXs, extracts features, processes the features through artificial intelligence, and interacts with the production process. The mEXs comprise sensors, conditioning circuits, and an analog/digital converter. They are responsible for acquiring field signals and their transmission to the mPP. The proposed system is designed for operating with electrical protection, allowing reliable operation of the mPP and mEXs. For evaluating and demonstrating the proposed system in a real scenario, we applied it in a case study for non-intrusive energy load disaggregation. © 2023 IEEE.

关键词： Cyber Physical System

来源：评论

学校读者我要写书评

暂无评论

Approaching Test Time Augmentation in the Context of Uncertainty Calibration for Deep Neural Networks

arXiv

引用

arXiv 2023年

作者： Conde, Pedro Barros, Tiago Lopes, Rui L. Premebida, Cristiano Nunes, Urbano J. The Institute of Systems and Robotics Department of Electrical and Computer Engineering University of Coimbra Portugal Critical Software South Africa

With the rise of Deep Neural Networks, machine learning systems are nowadays ubiquitous in a number of real-world applications, which bears the need for highly reliable models. This requires a thorough look not only at the accuracy of such systems, but also at their predictive uncertainty. Hence, we propose a novel technique (with two different variations, named M-ATTA and V-ATTA) based on test time augmentation, to improve the uncertainty calibration of deep models for image classification. By leveraging an adaptive weighting system, M/V-ATTA improves uncertainty calibration without affecting the model’s accuracy. The performance of these techniques is evaluated by considering diverse metrics related to uncertainty calibration, demonstrating their robustness. Empirical results, obtained on CIFAR-10, CIFAR-100, Aerial Image Dataset, as well as in two different scenarios under distribution-shift, indicate that the proposed methods outperform several state-of-the-art post-hoc calibration techniques. Furthermore, the methods proposed also show improvements in terms of predictive entropy on out-of-distribution samples. Code for M/V-ATTA available at: https://***/pedrormconde/MV-ATTA Copyright © 2023, The Authors. All rights reserved.

关键词： Calibration

来源：评论

学校读者我要写书评

暂无评论

Application of Deep Learning Method to Estimate Bottomhole Pressure Dynamics of Oil Wells 32

Application of Deep Learning Method to Estimate Bottomhole P...

引用

32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

作者： Cheng, Haibo Li, Shichao Zeng, Peng Vyatkin, Valeriy State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Luleå University of Technology Electrical and Space Engineering Department of Computer Science Luleå Sweden Aalto University Department of Electrical Engineering and Automation Helsinki Finland

ISBN: (纸本)9798350399714

Surrogate models, which have become an effective and popular method to close loop reservoir management problems, use a data-driven approach to predict dynamic injection and production wells parameters and optimize waterflooding development. In this study, a deep learning-based surrogate model method is proposed to estimate bottomhole pressure (BHP) of production wells in waterflooding reservoirs. Bidirectional long short-term memory (BiLSTM) network, as an efficient deep learning approach, is applied to BHP estimation using fluctuation data. Extended Fourier amplitude sensitivity test (EFAST) method is employed to analyse the influence of different input factors on BHP dynamics, and a reduced dataset is rebuilt to predict BHP parameter based on BiLSTM-EFAST algorithm. The estimation results are tested on a dataset from Volve oilfield in North Sea, and compared with other deep learning methods. The test results indicate that the proposed method can achieve higher prediction accuracy. A reduced dataset-based approach provides a new attempt to reduce model complexity and improve calculation speed for big data-driven surrogate model in oil and gas industry. © 2023 IEEE.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

Improving Lidar Based Tracking of UAVs Using an Approach Based on Focusing

Improving Lidar Based Tracking of UAVs Using an Approach Bas...

引用

Iberian robotics Conference (ROBOT)

作者： Alberto Cerutti Sedat Dogru Lino Marques Department of Electronics and Telecommunications (DET) Polytechnic University of Turin Turin Italy Department of Electrical and Computer Engineering Institute of Systems and Robotics University of Coimbra Coimbra Portugal

ISBN: (数字)9798350376364

ISBN: (纸本)9798350376371

This paper presents a novel approach for detecting drones using a lidar sensor integrated on a robotic turret. The turret rotates allowing the sensor to scan the sky, and both hardware components communicate in real-time. When the lidar sensor detects a drone, the detection data is used to dynamically adjust the motion pattern of the turret, allowing the system to capture more data by orienting the lidar sensor towards the drone, eventually improving tracking accuracy thanks to the higher number of detections achieved in this manner. In this paper we also explore different motion patterns for the turret, comparing them on the field to track a drone using the built lidar-turret system.

关键词： Laser radar Accuracy Uncertainty Tracking Focusing Robot sensing systems Real-time systems Hardware Optimization Drones

来源：评论

学校读者我要写书评

暂无评论

Camera Lidar Fusion for Unmanned Aerial Vehicle Detection

Camera Lidar Fusion for Unmanned Aerial Vehicle Detection

引用

Iberian robotics Conference (ROBOT)

作者： Cosimo Leuci Sedat Dogru Lino Marques Department of Electronics and Telecommunications (DET) Polytechnic University of Turin Turin Italy Department of Electrical and Computer Engineering Institute of Systems and Robotics University of Coimbra Coimbra Portugal

ISBN: (数字)9798350376364

ISBN: (纸本)9798350376371

Due to their low-cost and ease of use, cameras are very popular for drone detection. Thanks to the feature reach images obtained from the cameras, it is possible to classify drones with a relatively high success ratio. However, cameras lack the means for accurate localization, allowing only a rough measure of the orientation of the target UAV. In order to better localize the UAV, in this study we fuse camera and lidar measurements, localizing UAVs accurately. This fusion was implemented using a Kalman filter, which enables integration of both sensor data, improving detection and tracking accuracy

关键词： Location awareness YOLO Laser radar Accuracy Robot vision systems Cameras Autonomous aerial vehicles Kalman filters Vehicle dynamics Drones

来源：评论

学校读者我要写书评

暂无评论

Exploring Continuous Awareness Modelling for Improving Worker Safety and Trust*

Exploring Continuous Awareness Modelling for Improving Worke...

引用

IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Andrey Solovov Mohammad Zarei Vishal Gautam Bruno Ferreira Gustavo Assunção Antonio Marin-Hernandez Paulo Menezes Department of Electrical and Computer Engineering University of Coimbra Coimbra Portugal Institute of Systems and Robotics University of Coimbra Coimbra Portugal Universidad Veracruzana Xalapa Mexico

ISBN: (数字)9798350375022

ISBN: (纸本)9798350375039

The Industry 5.0 Human-Robot Interaction (HRI) goals have the potential for significantly reducing production costs, but require factory workers to trust that robots will not cause them physical harm when sharing the workspace in order to be achieved. To this end, we propose a model that adjusts the robot’s actions to an estimate of the workers’ awareness of its behavior. Its premise is that mutual awareness should be continuous, and if no recent visual contact has been established, then the robot should adapt its range of motion and speed in order to minimize the intersection between the robot’s space and the worker’s space. On the other hand, if the worker steadily establishes visual contact from times to times, the robot operates under a normal or a faster configuration. After a period of habituation, this awareness model can be further tweaked to continuously improve production times, while improving worker’s safety and trust. We present preliminary results of a pilot study with 32 participants, to asses if the existence of this awareness model impacts the outcomes of the combined task. The obtained tepidly optimistic results are the key to build upon in future designs.

关键词： Visualization Adaptation models Costs Service robots Human-robot interaction Production facilities Safety Motion control Fifth Industrial Revolution

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：