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检索条件"任意字段=2023 International Conference on Computer Science and Automation Technology, CSAT 2023"

共 68829 条记录，以下是631-640 订阅

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MRA-Depth: Multi-Resolution Attention based Monocular Depth Estimation 5

MRA-Depth: Multi-Resolution Attention based Monocular Depth ...

引用

5th international conference on Robotics and computer Vision, ICRCV 2023

作者： Wen, Jing Niu, Lukuan School of Computer Information and Technology Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education Shanxi University Taiyuan China School of Computer Information and Technology Shanxi University Taiyuan China

ISBN: (纸本)9798350326369

Delicate feature would become weaker or even disappear as going through deeper network layer, which results in jagged edges of objects in the depth estimation. To address this problem, we propose a multi-resolution attention based monocular depth estimation by capturing and recalibrating the dependencies of channels between different resolutions, including: we develop a multi-resolution attention encoder by embedding resolution and spatial attention, so as to extract the higher quality features in encoder, and we design a reusable multi-resolution fusion model in decoder, in which different scale features are integrated and then extract multi-resolution attention maps, so as to enhance detail information locally and perspective structure features globally. Experimental results illustrate the proposed network is capable to predict more precise depth and sharper contour, and to outperforms related methods on the KITTI benchmark. © 2023 IEEE.

关键词： Network layers

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A Rule and Network Dual-Driven Dynamic Scheduling Approach for Complex Flexible Manufacturing Job Shop 7

A Rule and Network Dual-Driven Dynamic Scheduling Approach f...

引用

7th international conference on Robotics, Control and automation Engineering, RCAE 2024

作者： Xu, Kai Xu, Binzi Huang, Dengchao Wang, Chun Anhui Polytechnic University School of Electrical Engineering Wuhu241000 China Huaibei Normal University School of Computer Science and Technology Huaibei235000 China

ISBN: (纸本)9798350355642

Traditional manually designed dispatching rules (DRs) cannot cope with the variety and rapid changes in production environments due to their inflexibility and lack of adaptability. Meanwhile, the development in manufacturing intelligence and informatization allows for storing a vast amount of scheduling data during production. Consequently, a novel approach emerges in constructing scheduling models and decision-making strategies based on historical data. Following this idea, this paper proposes a dual-driven dynamic scheduling approach for complex flexible manufacturing job shops, utilizing a combination of manually designed DRs and backpropagation neural network (BPNN) technology. Specifically, six different production scenarios are designed to optimize different objectives, simulating the actual complex manufacturing environment. Then, a real-time scheduling mapping network model is developed with the production states as input and selected DRs as output by training the BPNN. The results demonstrate the effectiveness and practicality of the proposed method in resolving dynamic scheduling issues of complex flexible manufacturing job shops, surpassing traditional manual DRs. © 2024 IEEE.

关键词： Flexible manufacturing systems

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An improved LIO-SAM lidar inertial odometer with dynamic point filtering 4

An improved LIO-SAM lidar inertial odometer with dynamic poi...

引用

2024 4th international conference on Mechatronics, automation and Intelligent Control, MAIC 2024

作者： Zhang, Hangtian Ma, Zhongli Zhang, Guoliang Liu, Jiajia College of Automation Chengdu University of Information Technology Sichuan Chengdu610000 China

LIO-SAM is an extensively utilized SLAM (Simultaneous Localization and Mapping) algorithm, featuring an integrated lidar-inertial odometry framework for high-precision, real-time trajectory estimation and mapping in mobile robots. In this paper, we integrate the lidar Iris loop detection algorithm into the LIO-SAM framework to solve the poor loop detection of LIO-SAM itself and the poor loop detection effect of Scan Context resulting from varying lidar directions passing through the same location. Additionally, an enhanced dynamic point filtering algorithm relying on ERASOR is developed to mitigate the presence of dynamic points in the point cloud map created by SLAM. Finally, validation with the KITTI dataset confirms the effectiveness of these algorithms, laying a robust foundation for further advancements. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： Mapping

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Automatic Concrete Surface Crack Recognition Using EfficientNetV2 Variants

Automatic Concrete Surface Crack Recognition Using Efficient...

引用

2023 international conference on System, Computation, automation and Networking, ICSCAN 2023

作者： Rama, A. Damasevicius, Robertas Arunmozhi, S. Mohammed, Mazin Abed Hussam, Ragheed Rajinikanth, V. Saveetha School of Engineering Simats Department of CSE TN Chennai602105 India Kaunas University of Technology Centre of Real Time Computer Systems Kaunas51423 Lithuania Manakula Vinayagar Institute of Technology Department of Electronics and Communication Engineering TN Puducherry605 107 India College of Computer Science and Information Technology University of Anbar Department of Artificial Intelligence Anbar31001 Iraq Al-farahidi University Medical Instruments Engineering Techniques Baghdad10021 Iraq Saveetha School of Engineering Simats Division of Research and Innovation Department of Computer Science and Engineering TN Chennai602105 India

ISBN: (纸本)9798350315127

Building health and structural integrity are important to ensure occupant safety and long-term durability. Monitoring and assessing building condition regularly ensures that potential problems are identified early. This research aims to develop and implement a deep-learning (DL) supported tool to examine the concrete surface images collected using digital camera. The data gathering forms the first stage and the chosen DL algorithm is used for feature extraction followed by the feature selection and then fusion is done and finally a fivefold cross verification schema is applied for a binary classification. This work considered the EfficientNetV2 (ENV2) model with variants like small, medium and large for the examination. The investigation is implemented using individual and fused deep-features and the performance of the developed tool is confirmed using the achieved accuracy. The outcome of this research confirms that the proposed tool produces a betterment of >96% accuracy with individual-features and 100% accuracy with fused-features. These results confirm that the proposed scheme provides significant result during the crack detection. © 2023 IEEE.

关键词： Crack detection

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Research on Elevator Group Control Algorithms 6

Research on Elevator Group Control Algorithms

引用

6th international conference on Internet of Things, automation and Artificial Intelligence, IoTAAI 2024

作者： Zheng, Fanghao Yao, Haobin Liang, Ruishi Tu, Mingjun University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu China University of Electronic Science and Technology of China Zhongshan Institute Zhongshan China University of Electronic Science and Technology of China Zhongshan Institute School of Computer Science Zhongshan China

ISBN: (纸本)9798350386974

Elevator group control algorithms constitute a vital component of intelligent building transportation management systems. This paper delves into the multidimensional challenges inherent in such algorithms: the uncertainty of passenger demand, striking a balance between energy efficiency and service quality, and the intricacy of the algorithms necessitating real-time execution. It provides a comprehensive review of the evolution and core challenges faced in elevator group control algorithms, with an emphasis on analyzing the characteristics, advantages, and limitations of various methodologies, including expert systems, fuzzy logic control, genetic algorithms, particle swarm optimization, neural networks, and reinforcement learning. The study concludes by casting a forward glance at the prospective trajectories of elevator group control technology, notably the promising prospects of group control algorithms that integrate reinforcement learning with deep neural networks. These advanced algorithms hold significant potential in enhancing transportation efficiency, facilitating energy conservation and emission reduction, as well as optimizing passengers' psychological waiting experience in elevators. © 2024 IEEE.

关键词： Energy efficiency

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A Prototype for Machine Learning Model Deployment in Cloud Environment

A Prototype for Machine Learning Model Deployment in Cloud E...

引用

2023 international conference on New Frontiers in Communication, automation, Management and Security, ICCAMS 2023

作者： Ramalakshmi, K. Agarwal, Aditya Gunasekaran, Hemalatha Khan, Sameer Ali Mandal, Nilesh Kumar Alliance University Computer Science & Engineering Bengaluru India University of Technology and Applied Sciences College of Computing and Information Sciences Ibri Oman

ISBN: (纸本)9798350317060

Training and developing a Machine Learning (ML) model is a difficult task, and then after successfully creating a working model, deploying and distribution is an added feature. In most instances, those models are never deployed. To help with this, we present a prototype, a SaaS platform to allow users to dynamically deploy their machine learning models to the cloud and host them so that the user has complete control over the visibility and *** delivery and deployment model provides lower upfront cost, timely updates, and a dedicated work/host environment. The platform's sole purpose revolves around the idea of a sharable deployable and ready to use Machine Learning Model. It takes advantage of the Continuous Integration and Continuous Delivery archetype facilitated by Kubernetes to dynamically provide custom and updated with the latest libraries docker environment. © 2023 IEEE.

关键词： Machine learning

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Design of Automatic Control System for Production of 700000 Ton High Speed Wire Rod

Design of Automatic Control System for Production of 700000 ...

引用

2023 international Seminar on computer science and Engineering technology, SCSET 2023

作者： Li, Guangjun Li, Haisheng Wang, Hui Beijing Vocational College of Labour and Social Security Beijing China Tongfang Energy Conservation Engineering Technology Co. Ltd. Beijing China

ISBN: (纸本)9798350301472

In order to achieve information sharing between field equipment on the one hand and more effectively complete control system tasks on the other, a set of distributed control systems based on Industrial Ethernet and PROFIBUS-DP fieldbus is created for a 700,000 ton high-speed wire automation production line in this paper. The ET200M distributed I/O station and industrial Ethernet are employed throughout the whole network system, efficiently resolving the control issues brought on by dispersed field equipment and rigorous control coordination needs. © 2023 IEEE.

关键词： automation

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Unbalanced Multi Classification Algorithm Combining Ensemble Learning and VAE

Unbalanced Multi Classification Algorithm Combining Ensemble...

引用

2023 international conference on Artificial Intelligence and automation Control, AIAC 2023

作者： Zhu, Shen Xu, Hua Yang, Chongyang College of Artificial Intelligence and Computer Science Wuxi China

ISBN: (纸本)9798350383805

A new algorithm based on Ensemble learning and Variational autoencoder (CBA-VAE) is proposed to solve the unbalanced multi classification problem. In imbalanced datasets, the number of minority class samples is significantly less than that of majority class samples, leading to a decrease in the performance of traditional classification algorithms. To solve this problem, Bagging technology is used to sample the original data set, generate multiple subsets, and increase the diversity of the base classifier. At the same time, by introducing Variational autoencoder (VAE) to reduce dimensions, we can learn the potential representation of data, extract effective features, and reduce the dimensions of data. In the experiment, the CBA-VAE algorithm was tested using multiple real-world datasets and compared with four algorithms. The experimental results show that the CBA-VAE algorithm is significantly superior to the comparison algorithm in terms of performance indicators such as AUC value and G-mean value. © 2023 IEEE.

关键词： Learning systems

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Research and Implementation Based on the eTPU 3

Research and Implementation Based on the eTPU

引用

3rd international conference on Artificial Intelligence, automation, and High-Performance Computing, AIAHPC 2023

作者： Wang, Ying Gao, Bo Li, Jinze Hao, Yibo Nation’s Research Laboratory of Computer Application Engineering Xi’an Aeronautics Computing Technique Research Institute AVIC Xi’an China Xi’an XinHang Talent Service Co. Ltd. Xi’an China

ISBN: (数字)9781510666580

ISBN: (纸本)9781510666573

As a special I/O channel in the control system, the eTPU (Enhanced Time Processing Unit) cooperates with the host computer to complete the corresponding functions. As the most foundational and important function in the eTPU, which is completed through I/O channel. This paper makes a comprehensive analysis of the thread entry and the pre-defined channel mode in the process of implementing the I/O function. Through the design of thread entry and the optimal selection of the pre-defined channel mode, the I/O function can be efficiently completed. By adopting clever design ideas and optimization, eTPU can provide more accurate and efficient functions. Especially through the implementation part of this article, the usage method of eTPU is more convenient to master. © 2023 SPIE.

关键词： computer control systems

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Visual Attention-Guided Weighted Naïve Bayes for Behavior Intention Inference 2

Visual Attention-Guided Weighted Naïve Bayes for Behavior I...

引用

2nd international conference on Artificial Intelligence, Human-computer Interaction and Robotics, AIHCIR 2023

作者： Pan, Chao Fang, Hongping Zhang, Hanyuan Wan, Zhonghua Mei, Ling Wu, Shiqian School of Information Science and Engineering Wuhan University of Science and Technology Wuhan China School of Machinery and Automation Wuhan University of Science and Technology Wuhan China

ISBN: (纸本)9798350360363

Intention inference based on eye gaze is an important issue in human-computer interaction. To address the issue of neglecting feature weight differences in behavior intention inference algorithms using visual attention objects as input features, a visual attention-guided weighted naïve Bayes behavior intention inference algorithm is proposed. Firstly, experiments are conducted to explore the eye-movement pattern for different behavioral intentions. Then, a method for quantifying visual attention using spatial-temporal features of eye-movement data is introduced. Finally, a visual attention prior weight matrix is constructed to guide the modified class-specific attribute weighted naïve Bayes model to learn the feature weights of different visual attention objects for achieving behavior intention inference. The experimental results show that the accuracy of the proposed method is 95.31%, which is at least 2.6% higher than the accuracy of the existing methods. At the same time, it can suppress the influence of visual attention noise objects to a certain extent, improving the robustness of the algorithm. © 2023 IEEE.

关键词： Eye movements

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