检索结果-内蒙古大学图书馆

arXiv 2023年

作者： Pereira, Ricardo Barros, Tiago Garrote, Luís Lopes, Ana Nunes, Urbano J. University of Coimbra Institute of Systems and Robotics Department of Electrical and Computer Engineering Portugal Polytechnic Institute of Tomar Portugal

This work proposes a novel approach that uses a semantic segmentation mask to obtain a 2D spatial layout of the segmentation-categories across the scene, designated by segmentation-based semantic features (SSFs). These features represent, per segmentation-category, the pixel count, as well as the 2D average position and respective standard deviation values. Moreover, a two-branch network, GS2F2App, that exploits CNN-based global features extracted from RGB images and the segmentation-based features extracted from the proposed SSFs, is also proposed. GS2F2App was evaluated in two indoor scene benchmark datasets: the SUN RGB-D and the NYU Depth V2, achieving state-of-the-art results on both datasets. © 2023, CC BY.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

A Depression Level Classification Model Based on EEG and GCN Network with Domain Generalization

A Depression Level Classification Model Based on EEG and GCN...

引用

第43届中国控制会议

作者： Zhongyi Zhang Chenyang Xu Licheng Jin Huirang Hou Qinghao Meng Tianjin Key Laboratory of Process Measurement and Control Institute of Robotics and Autonomous Systems School of Electrical and Information Engineering Tianjin University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Electroencephalography(EEG) contains a wealth of information, including neuron activity, allowing for a partial understanding of the brain's state. As a reliable tool, EEG, combined with deep neural networks, has been increasingly utilized to assist in the detection of depression and has achieved satisfactory results. However, there are still some limitations in the current models. Firstly, it is worth noting that many existing models are binary classification models. These models can determine whether a subject is depressed or not, but they lack the capability to differentiate the severity of depression. Besides, the variations in EEG signals among various individuals have not been thoroughly taken into account, leading to subpar performance when applying the trained model to new subjects. To address the aforementioned issues, we suggest implementing a multi-classification model that utilizes a graph convolutional neural network(GCN) to identify levels of depression. Additionally,to mitigate the problem of imbalanced samples in multi-classification tasks, we introduce a penalty coefficient for the smaller categories. At the same time, the issue of signal discrepancies among subjects was taken into account, leading to the introduction of the domain generalization module. Finally, the depression level identification task on the MODMA and PRED+CT dataset achieved an accuracy of 75.47% and 77.97% respectively, surpassing the performance of the state-of-the-art(SOTA) model. In addition, numerous ablation experiments were conducted to validate the efficacy of each module.

关键词： Depression Level EEG Graph Convolution Network Domain Generalization

来源：评论

学校读者我要写书评

暂无评论

Improving ASTRO's Perception Capability for a more Natural Follow-Me Task 6

Improving ASTRO's Perception Capability for a more Natural F...

引用

6th Experiment at International Conference, exp.at 2023

作者： Ferreira, Bruno Sorrentino, Alessandra Menezes, Paulo Batista, Jorge Dias, Jorge Fiorini, Laura Cavallo, Filipo University of Coimbra Institute of Systems and Robotics Dept. of Electrical and Computer Engineering Coimbra Portugal Khalifa University of Science and Technology Khalifa University Center for Autonomous Robotic Systems Abu Dhabi United Arab Emirates University of Florence Dept. of Industrial Engineering Florence Italy BioRobotics Institute Scuola Superiore Sant'Anna Pisa Italy

ISBN: (纸本)9798350314403

Social assistive robots usually encompass a great compromise between the advanced perception models that one can use and their computing capabilities. The ideal approaches are always oriented towards low power consumption while maintaining a higher order of responsiveness to the surroundings. Therefore, we present in this paper, an improvement of the follow-me system on ASTRO. In detail, we propose the use of Mediapipe SDK for human detection and tracking, when ASTRO is meant to accompany someone that is walking. A study on the new velocity and distance profiles that the robot keeps from the individuals is presented and we have also evaluated how it affects their perception of being safe. The presented results show that our new approach allows the system to achieve real-time performance by becoming ≈ 9.1× faster, smoothing, and keeping a more natural distance from the user. © 2023 IEEE.

关键词： Human robot interaction

来源：评论

学校读者我要写书评

暂无评论

AMG: A Depression Detection Model with Autoencoder and Multi-Head Graph Convolutional Network 42

AMG: A Depression Detection Model with Autoencoder and Multi...

引用

42nd Chinese Control Conference, CCC 2023

作者： Wang, Han-Guang Meng, Qing-Hao Jin, Li-Cheng Wang, Jian-Bang Hou, Hui-Rang Institute of Robotics and Autonomous Systems School of Electrical and Information Engineering Tianjin University Tianjin Key Laboratory of Process Measurement and Control Tianjin300072 China China Southern Power Grid Company Limited Guangzhou510623 China

ISBN: (纸本)9789887581543

Depression is a common chronic mental disorder characterized by high prevalence, recurrence, suicide rate, disability rate and heavy disease burden. Depression assessment based on questionnaires is subjective, therefore, a novel framework to is hereby designed to detect depression automatically and obj ectively. The framework first utilizes a two-way autoencoder to extract the hidden features from the original differential entropy features. The new features are used to generate the channel connectivity graph, using the multi-head attention mechanism. Next, the new features and graphs are input into the graph convolutional network (GCN) to aggregate spatial information. Finally, the output from GCN is passed to a fully connected layer and a soft layer to obtain the predicted label. Experiments are performed on Multimodal Open Dataset for Mental-disorder Analysis dataset. A final accuracy of 88.68% and a cross entropy loss of 2.4532 are obtained, when using ten-fold cross validation, outperforming other traditional machine learning methods including SVM, KNN, decision tree. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

Collision-Aware MPCC Integrated with Neural Augmentation for Quadrotor Trajectory Tracking

Collision-Aware MPCC Integrated with Neural Augmentation for...

引用

2025 IEEE International Conference on Mechatronics, ICM 2025

作者： Hu, Chuanqi Wang, Jin Chen, Yikai Chen, Yonghang Zheng, Zhi Meng, Jun Lu, Guodong Zhejiang University State Key Laboratory of Fluid Power and Mechatronic Systems Hangzhou310058 China Zhejiang University Zhejiang Key Laboratory of Industrial Big Data and Robot Intelligent Systems Hangzhou310058 China Robotics Research Center of Yuyao City Ningbo315400 China National Elite Institute of Engineering Chongqing University Chongqing401135 China School of Mechanical Engineering Zhejiang University Hangzhou310058 China College of Electrical Engineering Zhejiang University Hangzhou310027 China Center for Data Mining and Systems Biology College of Electrical Engineering Zhejiang University Hangzhou310027 China

ISBN: (纸本)9798331533892

This paper presents a trajectory tracking algorithm designed for autonomous quadrotors to navigate complex dy-namic environments that is resilient to collision disturbances. Since it combines Model Predictive Contouring Control (MPCC) with the capabilities of neural networks, our method is named MPCC Integrated with Neural Augmentation (MINA). By equip-ping the quadrotor with PVDF piezoelectric sensors, we achieve real-time perception of collision forces and utilize S4D-Conv Adaptive Net Architecture (SANA) for state computation, a network that integrates the advantages of S4D and convolutional kernels to enhance the accuracy of state predictions. We incorporate the predicted results into the MPCC framework to optimize the thrust output of the quadrotor for the next time step, ensuring precise trajectory tracking. Experimental validation demonstrates the reliability and effectiveness of our algorithm, providing an innovative solution for autonomous flight and trajectory tracking of quadrotors in complex dynamic environments. © 2025 IEEE.

关键词： Flight paths

来源：评论

学校读者我要写书评

暂无评论

Nonlinear Model Predictive Control for Optimal Dose Administration in Radiotherapy 15th

Nonlinear Model Predictive Control for Optimal Dose Administ...

引用

15th Advanced Doctoral Conference on Computing, electrical and Industrial systems, DoCEIS 2024

作者： Araújo, João C. G. Guerreiro, Bruno J. Oliveira, Luis B. da Silva, Filipe Ferreira CTS-UNINOVA and LASI Department of Electrical and Computer Engineering NOVA School of Science and Technology Caparica2829-516 Portugal Institute for Systems and Robotics LARSyS Lisbon1049-001 Portugal CEFITEC Department of Physics NOVA School of Science and Technology Caparica2829-516 Portugal

ISBN: (纸本)9783031638503

This work discusses the nonlinear modeling of healthy and cancer cell population growth under the influence of radiotherapy, and proposes predictive control techniques to determine the optimal dose for tumor control, while sparing surrounding healthy tissue. Radiation effects are modelled by a linear-quadratic formalism, coupled with a novel population-specific delayed dose response. Numerical simulations of the open- and closed-loop system are conducted, and robustness against model uncertainty is studied. Results illustrate the controller’s performance when dealing with imperfect information and unexpected system behavior, and how it can be tuned to produce the desired treatment outcome. However, optimal operation is conditioned by a limited prediction horizon, as well as strict adherence to treatment schedules and dose restrictions. © IFIP International Federation for Information Processing 2024.

关键词： Nonlinear systems

来源：评论

学校读者我要写书评

暂无评论

Design of Capsule Robot for Magnetic Gastric Biopsy and Drug Administration 20

Design of Capsule Robot for Magnetic Gastric Biopsy and Drug...

引用

20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Xu, Zhihui Li, Zongze Liu, Shoubin Hu, Chengzhi Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy Engineering Southern University of Science and Technology Shenzhen China Guangdong Prov. Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen China Harbin Institute of Technology School of Mechanical and Electrical Engineering Shenzhen China

ISBN: (纸本)9798350320831

Capsule robots have emerged as a promising tool for the early diagnosis of gastrointestinal diseases. Unlike conventional gastroscopy, they offer the potential for minimally invasive or even non-invasive treatment, and can alleviate discomfort and pain in patients. However, current capsule robots have some limitations. For instance, they lack stomach tissue biopsy and drug administration functions, and the capsule robot used for biopsy does not consider the tolerance of gastrointestinal tissue. Similarly, the capsule robot used for drug administration does not account for the outlet speed of drug administration. This paper proposes a new biopsy method using a magnetically manipulated capsule robot and analyzes the principles governing the robot's manipulation during the biopsy and drug administration processes. Furthermore, an ANSYS gastric model was established and used to simulate and experimentally analyze damage to the gastric tissue model from different types of biopsy needles and their moving speeds. The appropriate type of biopsy needle and moving speed were determined to prevent damage to the gastric tissue. The study also used FLUENT to determine the appropriate thrust at the entrance of the drug cavity and the impact of the drug density on the drug outlet velocity to ensure complete adherence of the drug to the lesion. © 2023 IEEE.

关键词： Biopsy

来源：评论

学校读者我要写书评

暂无评论

Global Trajectory Optimization for Autonomous Driving using Nonlinear Programming with Topology Classes*

Global Trajectory Optimization for Autonomous Driving using ...

引用

IEEE International Conference on Automation Science and engineering (CASE)

作者： Maryam Nezami Ngoc Thinh Nguyen Georg Schildbach Institute for Electrical Engineering in Medicine University of Lübeck (UzL) Lübeck Germany Institute for Robotics and Cognitive Systems UzL Lübeck Germany

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

Obstacle avoidance is an essential characteristic of autonomous driving cars. This paper presents a new method for efficiently determining possible routes that a vehicle can follow for overtaking obstacles and classifying them into different topology classes of paths. Impossible routes are eliminated based on the physical constraints of the vehicle. To evaluate each topology class and pick the one with the lowest cost as the globally optimal path, we run several topology-aided Nonlinear Programming (NLP) problems. For each topology-aided NLP problem to overtake the obstacles from the prespecified side determined by the topology class, corresponding auxiliary halfspace constraints are activated in the optimization problem. Through simulation results and comparisons with a standard NLP planner, we show that the overall computation time for solving several topology-aided NLP problems is faster than that of the standard NLP planner. Additionally, in complex driving scenarios, where the standard planner gets stuck in a sub-optimal solution due to internal faults or a local optimum, our proposed topology-aided planner can still find the globally optimal path.

关键词： Costs Simulation Roads Programming Topology Planning Collision avoidance Standards Autonomous vehicles Trajectory optimization

来源：评论

学校读者我要写书评

暂无评论

Camera and LiDAR Fusion for Robust 3D Person Detection in Indoor Environments

Camera and LiDAR Fusion for Robust 3D Person Detection in In...

引用

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

Portable Automatic Sensing System for Sustainable Precision Farm

Renewable Energy and Power Quality Journal

引用

Renewable Energy and Power Quality Journal 2022年 20卷 222-227页

作者： Galvão, J. Fernandes, J. Pereira, D. Galvão, M. Neves, F. Department of Electrical Engineering Polytechnic of Leiria Leiria2411-901 Portugal R&D Unit Institute for Systems Engineering and Computers INESC Coimbra Portugal ISTécnico/Lisbon Technical University Lisboa1049-001 Portugal Department of Computer Science Polytechnic of Leiria Leiria2411-901 Portugal

Taking into account the world´s growing population and climate change, there is a need to decarbonize production processes and, in particular, intensive cultures carried out in greenhouses. There is a need to boost the energy and water efficiency of these cyber-physical systems, taking into account human consumption or floriculture, as well as European Community (EEC) and United Nations agreements and pledges, such as the European Green Deal (EGD) or the REPowerEU Plan [1,2] t is critical to develop systems that use integrated models to control these sorts of intense production, collect physical variable factors more efficiently, and achieve improved and zero greenhouse gas emissions (GHG). Finally, it is crucial for a digitalization in these intensive crops, in precision farm or greenhouses. The main objective of this work focuses on the conception of a portable automatic sensing system (PASS) for pH, electroconductivity and water flow, to control irrigation water quality in precision farm/greenhouses. The data collected by these sensors are made available in a mobile app for consultation by the operator. Another objective will be the local production of electrical and thermal energy from renewable sources (solar and biomass), hybrid systems and the use of cogeneration to supply energy to the greenhouse. A sustainable product policy also has the potential to reduce waste significantly. © 2022, European Association for the Development of Renewable Energy, Environment and Power Quality (EA4EPQ). All rights reserved.

关键词： Sustainable development

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：