检索结果-内蒙古大学图书馆

IEEE Workshop on Applications of computer Vision (WACV)

作者： Raktim Gautam Goswami Naman Patel Prashanth Krishnamurthy Farshad Khorrami Department of Electrical and Computer Engineering Control/Robotics Research Laboratory (CRRL) NYU Tandon School of Engineering Brooklyn NY USA

ISBN: (数字)9798331510831

ISBN: (纸本)9798331510848

Map-free LiDAR localization systems accurately localize within known environments by predicting sensor position and orientation directly from raw point clouds, eliminating the need for large maps and descriptors. However, their long training times hinder rapid adaptation to new environments. To address this, we propose FlashMix, which uses a frozen, scene-agnostic backbone to extract local point descriptors, aggregated with an MLP mixer to predict sensor pose. A buffer of local descriptors is used to accelerate training by orders of magnitude, combined with metric learning or contrastive loss regularization of aggregated descriptors to improve performance and convergence. We evaluate FlashMix on various LiDAR localization benchmarks, examining different regularizations and aggregators, and demonstrating its effectiveness for rapid and accurate LiDAR localization in real-world scenarios. The code is available at https://***/raktimgg/FlashMix.

关键词： Location awareness Training Measurement Point cloud compression Laser radar Accuracy Pose estimation Benchmark testing Mixers Convergence

来源：评论

学校读者我要写书评

暂无评论

Switching event-triggered self-adjusting prescribed performance force control of electrohydraulic load simulator

引用

ISA Transactions 2025年

作者： Li, Jiafeng Ji, Ruihang Yan, Hao Shan, Jiefeng Chen, Zanwei School of Mechanical Electronic and Control Engineering Beijing Jiaotong University Beijing100044 China Department of Electrical and Computer Engineering National University of Singapore 117576 Singapore

This paper addresses the problem of switching event-triggered self-adjusting prescribed performance force control of electro-hydraulic load simulator (EHLS). A reduced-order fuzzy speed state observer for speed estimation is designed and a self-adjusting performance boundary is devised to mitigate the commutation jitter problem. The switching event-triggered mechanism dynamically adjusts the triggering conditions to optimize resource utilization. To reduce the complexity of the traditional inverse stepping control, the dynamic surface technique is adopted. The results demonstrate that the proposed control method guarantees the boundedness of the closed-loop system states and confines the tracking error to a small range near the equilibrium point within a finite time horizon. Finally, the effectiveness of the proposed method is demonstrated through experimentation. © 2025 International Society of Automation

关键词： Closed loop control systems

来源：评论

学校读者我要写书评

暂无评论

A Dimensional Difference-Based Population Size Adjustment Framework for Gannet Optimization Algorithm 16th

A Dimensional Difference-Based Population Size Adjustment Fr...

引用

16th International Conference on Genetic and Evolutionary Computing, ICGEC 2024

作者： Pan, Jeng-Shyang Han, Kunpeng Chu, Shu-Chuan Li, Zhi Zhang, Li College of Computer Science and Engineering Shandong University of Science and Technology Qingdao266590 China School of Artificial Intelligence Nanjing University of Information Science and Engineering Nanjing210044 China Department of Information Management Chaoyang University of Technology Taichung41349 Taiwan School of Information and Control Engineering Qingdao University of Technology Qingdao266590 China

ISBN: (纸本)9789819615346

In this paper, an improved Gannet optimization algorithm (DDPSA-GOA) is presented. The Gannet optimization algorithm (GOA) was formed by mathematically studying the various foraging behaviors of Gannet. GOA has had better results in the past. A framework DDPSA to improve GOA is cited in this paper. DDPSA aims to adjust population size and replace stagnant individuals with different strategies by determining the stage of the population. The framework divides the population into two stages, premature integration and evolutionary stagnation, which are two population states with stagnant individual replacement mechanisms. Optimal elimination replacement or elite replacement is adopted for different stages. The GOA algorithm in the DDPSA framework was tested against the initial GOA and other comparative algorithms in the CEC 2013 test set. Experimental results show that DDPSA-GOA outperforms other algorithms. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Optimization algorithms

来源：评论

学校读者我要写书评

暂无评论

Immoral post detection using a one-dimensional convolutional neural network-based LSTM network

引用

Multimedia Tools and Applications 2025年 1-20页

作者： Saqia, Bibi Khan, Khairullah Rahman, Atta Ur Khan, Aurangzeb Jain, Deepak Kumar Department of Computer Science University of Science and Technology Bannu28100 Pakistan Riphah Institute of Systems Engineering Riphah International University Islamabad46000 Pakistan Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Dalian116024 China Symbiosis Institute of Technology Symbiosis International University Pune India

In text mining and Natural Language Processing (NLP), extracting emotions from textual data is gaining rapid attraction. The proliferation of online content and the freedom of expression on social media platforms has compelled the advancement of more sophisticated methods for the automatic identification of unwanted content. The One-Dimensional Convolutional Neural Network (1D-CNN) performs best for feature extraction, while the Long Short-Term Memory Network (LSTM) is well-known for extracting sequential features and classification of textual data. This study proposes a novel solution by combining 1D-CNN with LSTM. Utilizing a context-aware model, this study aims to enhance the detection of immoral posts, including hate speech and other forms of immoral content on social media platforms. Various posts are extracted from social media, which are then processed using Glove word embedding models. It depicts the word representations in the text, which yields the form of a real-valued vector determining the words' meaning. The 1D convolution utilizes a filter window over the input time-series data to extract features. Relying on the acquired parameters of the filters, they act as feature extractors. This feature extraction technique allows the model to distinguish detailed patterns and nuances from the textual contents of posts. The sequential processing capabilities of the LSTM network enable an in-depth examination of the text, capturing temporal relationships and context, which is critical for successful content categorization. To validate the proposed model, we utilized a benchmark dataset, called the Twitter dataset. The proposed model achieved the highest accuracy of 95.37% and outperforms state-of-the-art works. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Special Session: D-MATE: A Design Methodology for Connecting Automatic Test Equipment in Industry 4.0

Special Session: D-MATE: A Design Methodology for Connecting...

引用

Latin American Test Workshop, LATW

作者： Francesco Biondani Francesco Tosoni Nicola Dall'Ora Enrico Fraccaroli Sara Vinco Dong Seon Cheng Franco Fummi Department of Engineering for Innovation Medicine Section of Engineering and Physics University of Verona (Italy) Department of Engineering Sciences Guglielmo Marconi University Italy Department of Control and Computer Engineering Politecnico di Torino Italy

ISBN: (数字)9781665477635

ISBN: (纸本)9781665477642

With the growing presence of semiconductor devices in healthcare, automotive, and consumer electronics, Automatic Test Equipment (ATE) systems play an increasingly vital role in ensuring quality and reliability during validation. Despite their importance, ATE systems often operate in isolation from other manufacturing processes, limiting interoperability and integration potential. Consequently, fully incorporating ATE systems within the Industry 4.0 framework remains a largely unaddressed challenge. To bridge this gap, we propose adopting Open Platform Communications Unified Architecture (OPC UA), the industry de-facto standard communication protocol for machines, with an accompanying specification tailored to ATE systems. We developed and validated our information model on an advanced ATE system, demonstrating its practical application. The results showcase the successful integration of the ATE system into a fully-fledged Industrial computer engineering (ICE) laboratory demonstrator. This study validates the effectiveness of our model in a real-world scenario and highlights the significance of our integration approach within the context of Industry 4.0.

关键词： Automatic test equipment Protocols Manufacturing processes Computational modeling Semiconductor devices Medical services Fourth Industrial Revolution Reliability Standards Manufacturing automation

来源：评论

学校读者我要写书评

暂无评论

Decoding Musical Evolution Through Network Science

arXiv

引用

arXiv 2025年

作者： Di Marco, Niccolò Loru, Edoardo Galeazzi, Alessandro Cinelli, Matteo Quattrociocchi, Walter Department of Computer Science Sapienza University of Rome Italy Department of Computer Control and Management Engineering Sapienza University of Rome Italy University of Padova Department of Mathematics Padova Italy

Music has always been central to human culture, reflecting and shaping traditions, emotions, and societal changes. Technological advancements have transformed how music is created and consumed, influencing tastes and the music itself. In this study, we use Network Science to analyze musical complexity. Drawing on ≈ 20, 000 MIDI files across six macro-genres spanning nearly four centuries, we represent each composition as a weighted directed network to study its structural properties. Our results show that Classical and Jazz compositions have higher complexity and melodic diversity than recently developed genres. However, a temporal analysis reveals a trend toward simplification, with even Classical and Jazz nearing the complexity levels of modern genres. This study highlights how digital tools and streaming platforms shape musical evolution, fostering new genres while driving homogenization and simplicity. © 2025, CC BY.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Tissue P Systems with Look-Ahead Mode

引用

Chinese Journal of Electronics 2025年第1期23卷 81-86页

作者： Yun Jiang Tao Song Zheng Zhang School of Computer Science and Information Engineering Chongqing Technology and Business University Chongqing China Department of Control Science and Engineering Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan China

Tissue P systems are a class of distributed and parallel computing models inspired from inter-cellular communication and cooperation between cells. In this work, a variant of tissue P system, named tissue P system with look-ahead mode, is discussed for decreasing the inherent non-determinism of tissue P systems and helping implementing tissue P systems on computers. Such systems are proved to be universal by simulating register machine, and they are also proved to be able to efficiently solve computationally hard problems by means of a space-time tradeoff, which is illustrated with a polynomial solution to 3-coloring problem.

关键词： computers Computational modeling Medical services Parallel processing Polynomials Computational efficiency Registers Business

来源：评论

学校读者我要写书评

暂无评论

Enhancing 6G-Satellite Network Integration with Artificial Intelligence: A Future Communication Paradigm 22

Enhancing 6G-Satellite Network Integration with Artificial I...

引用

22nd International Learning and Technology Conference, L and T 2025

作者： Salah, Ibrahim Hussein, Aziza I. Wageh Lotfy, Mostafa Mabrook, Mohamed Mourad Almaaqal University College of Engineering Control and Computer Department Basrah61001 Iraq Effat University College of Engineering Energy and Technology Research Center Saudi Arabia Faculty of Technology and Education Beni-Suef University Dept. of Process Control Technology Beni-Suef Egypt Beni-Suef University Faculty of Navigation Science & Space Technology Space Communication Dept. Beni-Suef Egypt

ISBN: (纸本)9798331532215

The integration of 6G networks and satellite communications is set to revolutionize global connectivity, offering seamless coverage across terrestrial and non-terrestrial environments. Artificial Intelligence (AI) is essential for improving this integration, addressing challenges such as dynamic resource management, latency reduction, and network optimization. AI techniques like machine learning, deep learning, and reinforcement learning offer innovative solutions to handle the complexities of 6G-satellite networks. These advancements promise to significantly improve network efficiency, enhance data transmission reliability, and ensure seamless connectivity across different areas. Potential use cases include smart cities, autonomous vehicles, and Internet of Things (IoT) applications, where AI-driven 6G-satellite integration will be crucial. The proposed AI-enhanced 6G-satellite framework not only addresses current challenges but also lays the groundwork for a resilient, scalable, and globally interconnected communication infrastructure, offering a promising future. © 2025 IEEE.

关键词： Satellite communication systems

来源：评论

学校读者我要写书评

暂无评论

CPL-SLAM: Centralized Collaborative Multi-Robot Visual-Inertial SLAM Using Point-and-Line Features

引用

IEEE Internet of Things Journal 2025年

作者： Liu, Xin Wen, Shuhuan Liu, Huaping Richard Yu, F. Yanshan University Engineering Research Center The Ministry of Education for Intelligent Control System and Intelligent Equipment Key Lab of Intelligent Rehabilitation and Neuroregulation in Hebei Province Department of Key Lab of Industrial Computer Control Engineering of Hebei Province Qinhuangdao066004 China Tsinghua University Department of Computer Science and Technology Beijing100084 China Shenzhen University College of Computer Science and Software Engineering China Carleton University Canada

Traditional visual-inertial SLAM (Simultaneous Localization and Mapping) systems predominantly rely on feature point matching from a single robot to realize the robot pose estimation and environment map construction. However, in complex scenarios, these traditional systems struggle with issues such as tracking failures due to illumination changes, rapid movements, and low-texture environments, and they perform poorly in terms of mapping efficiency and global consistency. To address these challenges, we propose a centralized collaborative SLAM system that employs both point and line features for tracking in the robot and map fusion in the cloud. The proposed system leverages the fusion of point and line features across all instances in the process, which allows our method to achieve higher localization accuracy in structured, low-texture scenes. With the aid of classifying gravity-aligned vertical lines and spatial parallel lines, the proposed system can deliver faster and more accurate odometry in complex scenes. Furthermore, we developed intra-robot and inter-robot loop closure detection methods based on point and line features, generating a globally consistent sparse point cloud and structured scene map in the cloud. Our method is able to build richer maps while improving accuracy compared to existing methods. Experimental results on public datasets and in real-world environments show that, compared to existing advanced methods, our approach demonstrates better performance. © 2014 IEEE.

关键词： SLAM robotics

来源：评论

学校读者我要写书评

暂无评论

Locate N’ Rotate: Two-Stage Openable Part Detection with Foundation Model Priors 17th

Locate N’ Rotate: Two-Stage Openable Part Detection with F...

引用

17th Asian Conference on computer Vision, ACCV 2024

作者： Li, Siqi Chen, Xiaoxue Cheng, Haoyu Zhou, Guyue Zhao, Hao Tian, Guanzhong Ningbo innovation Center Zhejiang University Hangzhou China College of Control Science and Engineering Zhejiang University Hangzhou China Institute for AI Industry Research Tsinghua University Beijing China Department of Computer Science and Technology Tsinghua University Beijing China

ISBN: (纸本)9789819609628

Detecting the openable parts of articulated objects is crucial for downstream applications in intelligent robotics, such as pulling a drawer. This task poses a multitasking challenge due to the necessity of understanding object categories and motion. Most existing methods are either category-specific or trained on specific datasets, lacking generalization to unseen environments and objects. In this paper, we propose a Transformer-based Openable Part Detection (OPD) framework named Multi-feature Openable Part Detection (MOPD) that incorporates perceptual grouping and geometric priors, outperforming previous methods in performance. In the first stage of the framework, we introduce a perceptual grouping feature model that provides perceptual grouping feature priors for openable part detection, enhancing detection results through a cross-attention mechanism. In the second stage, a geometric understanding feature model offers geometric feature priors for predicting motion parameters. Compared to existing methods, our proposed approach shows better performance in both detection and motion parameter prediction. Codes and models are publicly available at https://***/lisiqi-zju/MOPD. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Intelligent robots

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：