检索结果-内蒙古大学图书馆

International Symposium on Medical robotics (ISMR)

作者： Tae Wan Kim Haoying Zhou Juan Antonio Barragan Hisashi Ishida Peter Kazanzides Adnan Munawar Department of Computer Science Johns Hopkins University Baltimore MD USA Department of Biomedical Engineering Johns Hopkins University Baltimore MD USA Laboratory for Computational Sensing and Robotics Johns Hopkins University Baltimore MD USA Department of Robotics Engineering Worcester Polytechnic Institute Worcester MA USA

ISBN: (数字)9798331599003

ISBN: (纸本)9798331599010

Virtual simulations have served as important tools to design and test robotic frameworks in a variety of domains. Increasingly, they have been used to train and experiment on surgical robotics applications. Having seen the success of an open simulation environment for robot-assisted surgical suturing in the Asynchronous Multi-Body Framework (AMBF), we sought to reproduce the surgical suturing environment from AMBF in NVIDIA Isaac Sim, a new simulator with impressive visual fidelity and GPU-accelerated computation capabilities. We present a virtual scene for robotic suturing comprising two robotic manipulators, an endoscope, two surgical phantoms, and a needle attached to a thread. The thread is modeled using three different techniques. This work also provides interactive manipulation of the virtual scene via haptic input devices using the Robot Operating System interface. We measured performance speeds, ranging between 13 to 60 frames per second depending on the task, and approximately 0.5 seconds of delay between a haptic input device and the simulator. In this environment, we hope to provide a descriptive overview of the capabilities and limitations of NVIDIA Isaac Sim for surgical simulation applications.

关键词： Performance evaluation Visualization Medical robotics Instruction sets Computational modeling Operating systems Input devices Phantoms Needles Haptic interfaces

来源：评论

学校读者我要写书评

暂无评论

Allocation and Migration of Virtual Machines Using Machine Learning

引用

computers, Materials & Continua 2022年第2期70卷 3349-3364页

作者： Suruchi Talwani Khaled Alhazmi Jimmy Singla Hasan JAlyamani Ali Kashif Bashir School of Computer Science&Engg. Lovely Professional UniversityPunjabIndia National Center for Robotics and Internet of Things Technology Communication and Information Technology Research InstituteKing Abdulaziz City for Science and Technology(KACST)Riyadh11442Saudi Arabia Department of Information Systems Faculty of Computing and Information Technology in RabighKing Abdulaziz UniversityRabigh21911Saudi Arabia Department of Computing and Mathematics ManchesterMetropolitan UniversityManchesterM156BHUK

Cloud computing promises the advent of a new era of service boosted by means of virtualization *** process of virtualization means creation of virtual infrastructure,devices,servers and computing resources needed to deploy an application *** extensively practiced technology involves selecting an efficient Virtual Machine(VM)to complete the task by transferring applications from Physical Machines(PM)to VM or from VM to *** whole process is very challenging not only in terms of computation but also in terms of energy and *** research paper presents an energy aware VM allocation and migration approach to meet the challenges faced by the growing number of cloud data *** Learning(ML)based Artificial Bee Colony(ABC)is used to rank the VM with respect to the load while considering the energy efficiency as a crucial *** most efficient virtual machines are further selected and thus depending on the dynamics of the load and energy,applications are migrated fromoneVMto *** simulation analysis is performed inMatlab and it shows that this research work results in more reduction in energy consumption as compared to existing studies.

关键词： Cloud computing VM allocation VM migration machine learning

来源：评论

学校读者我要写书评

暂无评论

Comparison of Rating Scale and Pairwise Comparison Methods for Measuring Human Co-worker Subjective Impression of Robot during Physical Human-Robot Collaboration

Comparison of Rating Scale and Pairwise Comparison Methods f...

引用

IEEE International Conference on robotics and Automation (ICRA)

作者： Qiao Wang Ziqi Wang Marc G. Carmichael Dikai Liu Chin-Teng Lin Robotics Institute Faculty of Engineering and Information Technology University of Technology Sydney Ultimo NSW Australia Australian Artificial Intelligence Institute School of Computer Science Faculty of Engineering and Information Technology University of Technology Sydney Ultimo NSW Australia

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

The Rating Scale method has been long deemed the standard for measuring subjective perceptions. However, in the field of physical human-robot collaboration (pHRC), its aptness should be put under scrutiny due to inherent challenges such as response bias, between-subject variations, and the granularity *** variances can introduce significant bias in the rating scale results. A high granularity in the scale could overwhelm participants, leading to unclear and biased responses, while a low granularity may gloss over the fine nuances of human feelings. Additionally, there’s a notable risk of receiving careless responses, which compromise data reliability. Recognizing these challenges, this paper proposes the application of Pairwise Comparison (PC) in pHRC — an alternative survey technique that emphasizes direct comparisons between items on the defined criteria. By using the NASA Task Load Index (NASA-TLX) as a template, RS and PC questionnaires are designed and used in a series of pHRC experiments. Our preliminary findings suggest that PC is more precise and robust than the rating scale method. Compared to RS, PC fosters authentic participant interests in the experiment by intuitive question design and reducing the experimental duration. Besides, the accuracy and reliability of PC are also found to be consistent regardless of the variations in our experimental procedure design.

关键词： Surveys Accuracy NASA Collaboration Reliability engineering Particle measurements Task analysis

来源：评论

学校读者我要写书评

暂无评论

Fingerprint Presentation Attack Detector Using Global-Local Model

arXiv

引用

arXiv 2024年

作者： Liu, Haozhe Zhang, Wentian Liu, Feng Wu, Haoqian Shen, Linlin The Computer Vision Institute College of Computer Science and Software Engineering SZU Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society The National Engineering Laboratory for Big Data System Computing Technology The Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen518060 China

The vulnerability of automated fingerprint recognition systems (AFRSs) to presentation attacks (PAs) promotes the vigorous development of PA detection (PAD) technology. However, PAD methods have been limited by information loss and poor generalization ability, resulting in new PA materials and fingerprint sensors. This paper thus proposes a global-local model-based PAD (RTK-PAD) method to overcome those limitations to some extent. The proposed method consists of three modules, called: 1) the global module;2) the local module;and 3) the rethinking module. By adopting the cut-out-based global module, a global spoofness score predicted from nonlocal features of the entire fingerprint images can be achieved. While by using the texture in-painting-based local module, a local spoofness score predicted from fingerprint patches is obtained. The two modules are not independent but connected through our proposed rethinking module by localizing two discriminative patches for the local module based on the global spoofness score. Finally, the fusion spoofness score by averaging the global and local spoofness scores is used for PAD. Our experimental results evaluated on LivDet 2017 show that the proposed RTK-PAD can achieve an average classification error (ACE) of 2.28% and a true detection rate (TDR) of 91.19% when the false detection rate (FDR) equals 1.0%, which significantly outperformed the state-of-the-art methods by ∼10% in terms of TDR (91.19% versus 80.74%). Copyright © 2024, The Authors. All rights reserved.

关键词： Supervised learning

来源：评论

学校读者我要写书评

暂无评论

AirShot: Efficient Few-Shot Detection for Autonomous Exploration

arXiv

引用

arXiv 2024年

作者： Wang, Zihan Li, Bowen Wang, Chen Scherer, Sebastian Institute for Imaging Data and Communications School of Engineering The University of Edinburgh United Kingdom AirLab Robotics Institute Carnegie Mellon University PittsburghPA15213 United States Lab Institute for Artificial Intelligence and Data Science Department of Computer Science and Engineering University at Buffalo NY14260 United States

Few-shot object detection has drawn increasing attention in the field of robotic exploration, where robots are required to find unseen objects with a few online provided examples. Despite recent efforts have been made to yield online processing capabilities, slow inference speeds of low-powered robots fail to meet the demands of real-time detection-making them impractical for autonomous exploration. Existing methods still face performance and efficiency challenges, mainly due to unreliable features and exhaustive class loops. In this work, we propose a new paradigm AirShot, and discover that, by fully exploiting the valuable correlation map, AirShot can result in a more robust and faster few-shot object detection system, which is more applicable to robotics community. The core module Top Prediction Filter (TPF) can operate on multi-scale correlation maps in both the training and inference stages. During training, TPF supervises the generation of a more representative correlation map, while during inference, it reduces looping iterations by selecting top-ranked classes, thus cutting down on computational costs with better performance. Surprisingly, this dual functionality exhibits general effectiveness and efficiency on various off-the-shelf models. Exhaustive experiments on COCO2017, VOC2014, and SubT datasets demonstrate that TPF can significantly boost the efficacy and efficiency of most off-the-shelf models, achieving up to 36.4% precision improvements along with 56.3% faster inference speed. Code and Data are at: https://***/ImNotPrepared/AirShot. Copyright © 2024, The Authors. All rights reserved.

关键词： Efficiency

来源：评论

学校读者我要写书评

暂无评论

Interpreting Deep Convolutional Neural Networks for Medical Diagnosis Using Perceptual Encoding and Retrieval

Interpreting Deep Convolutional Neural Networks for Medical ...

引用

International Conference on Computing and Networking Technology (ICCNT)

作者： Shreyas Kasture Sudhanshu Maurya Rohan Verma Ajay Kumar Yadav Amit Shukla Symbiosis Institute of Technology Nagpur Campus Symbiosis International (Deemed University) Pune India Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun India Department of Computer Application United Institute of Management Prayagraj India Centre of Artificial Intelligence & Robotics Indian Institute of Technology (IIT) Mandi India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

The robust performance of deep neural networks (DNNs) in many areas, including medical diagnosis, is not accessible from the problem of interpretability. Even though DNNs have high accuracy, they tend to operate as black boxes, usually without any explanation of which basis their predictions are made. This interpretability issue has become important, especially for high-stakes applications, such as medical image analysis and disease diagnosis, in which people’s lives are at risk. The study was structured to raise novel approaches for DNNs, internal representation translation and provide visualizations to assist medical diagnosis tasks and ensure reliable and transparent decision-making procedures. Such techniques have been developed to improve the interpretability of DNN without sacrificing the performance. The models for proposed models succeeded in the clinical tasks of medical diagnosis. They reached competitive accuracy with the best model, obtaining an accuracy of 95.7% and an F1-score of 0.914 on lung abnormality detection from chest X-rays. AUC-ROC high sensitivity and specificity of 0.963 were observed when diagnosing brain tumors based on MRI scans. These models also provided improved faithfulness perceived through saliency maps, which had an average score of 0.82, and concept activation vectors, with a consistency of 0.77 from the evaluation done by medical experts. The suggested methods offer a chance for a better patient outcome via high-precision and safe diagnostics and treatment options with an expected change in misdiagnosis rate of 10-15%.

关键词： Ethics Accuracy Decision making Brain modeling Vectors Medical diagnosis Reliability Artificial intelligence Medical diagnostic imaging X-ray imaging

来源：评论

学校读者我要写书评

暂无评论

Exploring the Potential of LLM-based Chatbots for Task Scheduling in Robot Operations 25

Exploring the Potential of LLM-based Chatbots for Task Sched...

引用

25th IEEE International Conference on Autonomous Robot Systems and Competitions, ICARSC 2025

作者： Rema, Catarina Sousa, Armando Sobreira, Heber Costa, Pedro Silva, Manuel F. Faculty of Engineering Porto4200-465 Portugal INESC TEC - Institute for Systems and Computer Engineering Technology and Science CRIIS - Centre for Robotics in Industry and Intelligent Systems Porto4200-465 Portugal ISEP Polytechnic of Porto rua Dr. António Bernardino de Almeida Porto4249-015 Portugal

ISBN: (纸本)9798331538606

The rise of Industry 4.0 has revolutionized manufacturing by integrating real-time data analysis, artificial intelligence (AI), automation, and interconnected systems, enabling adaptive and resilient smart factories. Autonomous Mobile Robots (AMRs), with their advanced mobility and navigation capabilities, are a pillar of this transformation. However, their deployment in job shop environments adds complexity to the already challenging Job Shop Scheduling Problem (JSSP), expanding it to include task allocation, robot scheduling, and travel time optimization, creating a multi-faceted, non-deterministic polynomial-time hardness (NP-hard) problem. Traditional approaches such as heuristics, meta-heuristics, and mixed integer linear programming (MILP) are commonly used. Recent AI advancements, particularly large language models (LLM), have shown potential in addressing these scheduling challenges due to significant improvements in reasoning and decision-making from textual data. This paper examines the application of LLM to tackle scheduling complexities in smart job shops with mobile robots. Guided by tailored prompts inserted manually, LLM are employed to generate scheduling solutions, being these compared to an heuristic-based method. The results indicate that LLM currently have limitations in solving complex combinatorial problems, such as task scheduling with mobile robots. Due to issues with consistency and repeatability, they are not yet reliable enough for practical implementation in industrial environments. However, they offer a promising foundation for augmenting traditional approaches in the future. © 2025 IEEE.

关键词： Integer programming

来源：评论

学校读者我要写书评

暂无评论

Data-Driven Latent Space Representation for Robust Bipedal Locomotion Learning

Data-Driven Latent Space Representation for Robust Bipedal L...

引用

IEEE International Conference on robotics and Automation (ICRA)

作者： Guillermo A. Castillo Bowen Weng Wei Zhang Ayonga Hereid Electrical and Computer Engineering Ohio State University Columbus OH USA Department of Computer Science Iowa State University Ames IA USA SUSTech Institute of Robotics Southern University of Science and Technology (SUSTech) China Mechanical and Aerospace Engineering Ohio State University Columbus OH USA

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

This paper presents a novel framework for learning robust bipedal walking by combining a data-driven state representation with a Reinforcement Learning (RL) based locomotion policy. The framework utilizes an autoencoder to learn a low-dimensional latent space that captures the complex dynamics of bipedal locomotion from existing locomotion data. This reduced dimensional state representation is then used as states for training a robust RL-based gait policy, eliminating the need for heuristic state selections or the use of template models for gait planning. The results demonstrate that the learned latent variables are disentangled and directly correspond to different gaits or speeds, such as moving forward, backward, or walking in place. Compared to traditional template model-based approaches, our framework exhibits superior performance and robustness in simulation. The trained policy effectively tracks a wide range of walking speeds and demonstrates good generalization capabilities to unseen scenarios.

关键词： Legged locomotion Training Manifolds Supervised learning Reinforcement learning Aerospace electronics Robustness

来源：评论

学校读者我要写书评

暂无评论

A Wearable Eye-Tracking Approach for Early Autism Detection with Machine Learning: Unravelling Challenges and Opportunities

A Wearable Eye-Tracking Approach for Early Autism Detection ...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： J. Lopez-Martinez Purificación Checa José Manuel Soto-Hidalgo Isaac Triguero Alberto Fernández Department of Computer Science and Artificial Intelligence University of Granada Spain Dept. of Educational and Evolutive Psychology University of Granada Spain Dept. of Comput. Eng. Automation and Robotics University of Granada Spain DaSCI Andalusian Institute in Data Science and Computational Intelligence School of Computer Science University of Nottingham Nottingham UK

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Early detection of Autism Spectrum Disorder (ASD) is crucial to facilitate timely interventions, improve outcomes, and enhance the quality of life for individuals on the spectrum. Artificial intelligence and machine learning have significantly advanced the study of ASD by enabling sophisticated analyses of complex behavioural data, providing more accurate and timely detection methods. Nevertheless, existing research is mostly focused on either screening manual methods via psychological surveys, and/or the application of functional Magnetic Resonance Imaging. In the former case, there is a limitation due the subjectivity of the procedure; whereas in the latter the high cost represents a barrier to widespread use in diagnosis. In consideration of the aforementioned factors, this research contributes significantly to the field by integrating commodity wearable technology with psycho-healthcare, employing eye-tracking capabilities as a novel, non-invasive approach for early ASD diagnosis. Our methodology stands out by offering a comprehensive, four-step process that includes sophisticated image preprocessing, innovative feature extraction, precise classification, and a novel multi-instance aggregation strategy. We show its potential via a compelling case study that attests to the feasibility and efficacy of this innovative paradigm. Additionally, the work underscores prevailing challenges in the field, stressing some factors such as the acquisition of extensive and diverse datasets to allow for a multi-modal approach and the application of Trustworthy Artificial Intelligence.

关键词： Surveys Autism Neural networks Psychology Machine learning Gaze tracking Manuals

来源：评论

学校读者我要写书评

暂无评论

Functional Equivalence with NARS

arXiv

引用

arXiv 2024年

作者： Johansson, Robert Hammer, Patrick Lofthouse, Tony Department of Psychology Stockholm University Sweden Department of Computer and Information Science Linköping University Linköping Sweden Division of Robotics Perception and Learning KTH Royal Institute of Technology Stockholm Sweden

This study explores the concept of functional equivalence within the framework of the Non-Axiomatic Reasoning System (NARS), specifically through OpenNARS for Applications (ONA). Functional equivalence allows organisms to categorize and respond to varied stimuli based on their utility rather than perceptual similarity, thus enhancing cognitive efficiency and adaptability. In this study, ONA was modified to allow the derivation of functional equivalence. This paper provides practical examples of the capability of ONA to apply learned knowledge across different functional situations, demonstrating its utility in complex problem-solving and decision-making. An extended example is included, where training of ONA aimed to learn basic human-like language abilities, using a systematic procedure in relating spoken words, objects and written words. The research carried out as part of this study extends the understanding of functional equivalence in AGI systems, and argues for its necessity for level of flexibility in learning and adapting necessary for human-level AGI. © 2024, CC BY-NC-ND.

关键词： Decision making

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：