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arXiv 2024年

作者： Yang, Haodong Xu, Jisheng Lin, Zhiliang He, Jianping The Department of Computer Science Shanghai Jiao Tong University China The Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China The School of Ocean and Civil Engineering Shanghai Jiao Tong University State Key Laboratory of Ocean Engineering Shanghai200240 China

Computer vision techniques have empowered underwater robots to effectively undertake a multitude of tasks, including object tracking and path planning. However, underwater optical factors like light refraction and absorption present challenges to underwater vision, which cause degradation of underwater images. A variety of underwater image enhancement methods have been proposed to improve the effectiveness of underwater vision perception. Nevertheless, for real-time vision tasks on underwater robots, it is necessary to overcome the challenges associated with algorithmic efficiency and real-time capabilities. In this paper, we introduce Lightweight Underwater Unet (LU2Net), a novel U-shape network designed specifically for real-time enhancement of underwater images. The proposed model incorporates axial depthwise convolution and the channel attention module, enabling it to significantly reduce computational demands and model parameters, thereby improving processing speed. The extensive experiments conducted on the dataset and real-world underwater robots demonstrate the exceptional performance and speed of proposed model. It is capable of providing well-enhanced underwater images at a speed 8 times faster than the current state-of-the-art underwater image enhancement method. Moreover, LU2Net is able to handle real-time underwater video enhancement. Copyright © 2024, The Authors. All rights reserved.

关键词： Motion planning

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Exploring Stronger Feature for Temporal Action Localization

arXiv

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arXiv 2021年

作者： Qing, Zhiwu Wang, Xiang Huang, Ziyuan Feng, Yutong Zhang, Shiwei Jiang, Jianwen Tang, Mingqian Gao, Changxin Sang, Nong Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology China Alibaba Group China

Temporal action localization aims to localize starting and ending time with action category. Limited by GPU memory, mainstream methods pre-extract features for each video. Therefore, feature quality determines the upper bound of detection performance. In this technical report, we explored classic convolution-based backbones and the recent surge of transformer-based backbones. We found that the transformer-based methods can achieve better classification performance than convolution-based, but they cannot generate accuracy action proposals. In addition, extracting features with larger frame resolution to reduce the loss of spatial information can also effectively improve the performance of temporal action localization. Finally, we achieve 42.42% in terms of mAP on validation set with a single SlowFast [9] feature by a simple combination: BMN [16]+TCANet [19], which is 1.87% higher than the result of 2020 [20]’s multi-model ensemble. Finally, we achieve Rank 1st on the CVPR2021 HACS supervised Temporal Action Localization Challenge. Copyright © 2021, The Authors. All rights reserved.

关键词： Convolution

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Optimal Design of Work Quantification System 16th

Optimal Design of Work Quantification System

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16th International Conference on intelligent Information Hiding and Multimedia Signal processing, IIH-MSP 2020 in conjunction with the 13th International Conference on Frontiers of Information Technology, Applications and Tools, FITAT 2020

作者： Liu, Lei Lin, Wenru Huang, Yingcong Software College Minjiang University Fuzhou350121 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350121 China School of Computer and Control Engineering Minjiang University Fuzhou350121 China

ISBN: (纸本)9789813367562

In view of the requirements of the correctness of quantitative results, the dynamic variety of quantitative rules and collaborative result recording in data management, the work quantification system is analyzed and optimized. The core module of the work quantification is designed by using the features of dynamic parsing script provided by JavaScript engine, and finally, a set of applicative, efficient, and expandable work quantification system is developed. The application of the system will bring convenience to all users due to its effective data management. In addition, easy access to the fast Internet makes the analysis and use of achievement data more efficient. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021.

关键词： Information management

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control Strategy of Multi-axis Serial Manipulator Based on Improved Active Disturbance Rejection control

Control Strategy of Multi-axis Serial Manipulator Based on I...

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第34届中国控制与决策会议

作者： Pengcheng Hu Chaochen Gu Kaijie Wu Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information ProcessingMinistry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management

Aiming at the sudden change of load torque and uncertain external disturbance that multi-axis serial manipulators may face during operation,an improved Active Disturbance Rejection controller(ADRC) assisted by a Nonlinear Disturbance Observer(NLDOB) is designed and implemented in this *** realizes the estimation and compensation of known model parameter perturbation,and NLDOB is introduced to estimate and compensate the load torque and other unmodeled dynamic factors of the ***,the lumped control object model of three-bar mechanism and permanent magnet DC motor is established,and the control response curves of improved ADRC,traditional ADRC,and PID under the same conditions are compared and analyzed through *** experimental results show that compared with the traditional ADRC and PID,the improved ADRC has faster response speed,smaller overshoot and stronger robustness.

关键词： ADRC Multi-axis serial manipulator Permanent magnet DC motor NLDOB Load estimation

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Construction of Three-Dimensional Nickel-Vanadium Hydrotalcite with Ball-Flower Architecture for Screen-Printed Asymmetric Supercapacitor

SSRN

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SSRN 2022年

作者： Tu, Qian Zhang, Qiang Sun, Xinyu Wang, Jinglu Lin, Baoying Liu, Jin Liu, Zhonghua Chen, Liangzhe School of Electronic Information Engineering Jingchu University of Technology Jingmen448000 China School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry Huazhong University of Science and Technology Wuhan430074 China

As a promising energy storage matter, two-dimensional (2D) layered double hydroxides (LDHs) suffer from a lower specific capacitance and poor retention. Morphology engineering is deemed to be an effective means. Herein, three-dimensional (3D) nickel-vanadium hydrotalcite (NiV-LDHs) with ball-flower structure are synthesized successfully via a facile dynamic-refluxing route, such a green strategy dispenses with template and high pressure and generates a specific surface area as high as 61.6 m 2 /g. Then, the screen-printed inks with outstanding rheological performances are formulated and the resulting electrodes display superior hydrophilic performance. Benefitted from the 3D architecture and shear flow process, the NiV-LDHs electrode can deliver an enhanced specific capacitance of 1069 F/g at 1 A/g with cycling stability of ~68.0% after 1500 cycles at 20 A/g, in contrast with that of NiV-LDHs prepared by coprecipitation (848 F/g and ~5.1%). Furthermore, an asymmetric NiV-LDHs//activated carbon supercapacitor (ASC) is assembled, which can yield a remarkable energy density of 75.8 μWh/cm2 at a power density of 0.80 mW/cm2, and two ASCs in series can illuminate a red light (2.5 V) for more than 270 s. Therefore, this study proposes a facile and economic strategy to prepare 3D nanomaterial for advanced and flexible printable energy storage devices. © 2022, The Authors. All rights reserved.

关键词： Screen printing

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Proposal relation network for temporal action detection

arXiv

引用

arXiv 2021年

作者： Wang, Xiang Qing, Zhiwu Huang, Ziyuan Feng, Yutong Zhang, Shiwei Jiang, Jianwen Tang, Mingqian Gao, Changxin Sang, Nong Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology China Alibaba Group China

This technical report presents our solution for temporal action detection task in AcitivityNet Challenge 2021. The purpose of this task is to locate and identify actions of interest in long untrimmed videos. The crucial challenge of the task comes from that the temporal duration of action varies dramatically, and the target actions are typically embedded in a background of irrelevant activities. Our solution builds on BMN [10], and mainly contains three steps: 1) action classification and feature encoding by Slowfast [6], CSN [13] and ViViT [1];2) proposal generation. We improve BMN by embedding the proposed Proposal Relation Network (PRN), by which we can generate proposals of high quality;3) action detection. We calculate the detection results by assigning the proposals with corresponding classification results. Finally, we ensemble the results under different settings and achieve 44.7% on the test set, which improves the champion result in ActivityNet 2020 [17] by 1.9% in terms of average mAP. Copyright © 2021, The Authors. All rights reserved.

关键词： Machine learning

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A novel dataset and a two-stage mitosis nuclei detection method based on hybrid anchor branch

arXiv

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arXiv 2023年

作者： Wang, Huadeng Xu, Hao Li, Bingbing Pan, Xipeng Zeng, Lingqi Lan, Rushi Luo, Xiaonan School of Computer Science and Information Security Guilin University of Electronic Technology Guilin541004 China Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin541004 China Department of Pathology Ganzhou Municipal Hospital Ganzhou341000 China

Mitosis detection is one of the challenging problems in computational pathology, and mitotic count is an important index of cancer grading for pathologists. However, current counts of mitotic nuclei rely on pathologists looking microscopically at the number of mitotic nuclei in hot spots, which is subjective and time-consuming. In this paper, we propose a two-stage cascaded network, named FoCasNet, for mitosis detection. In the first stage, a detection network named Mdet is proposed to detect as many mitoses as possible. In the second stage, a classification network Mclass is proposed to refine the results of the first stage. In addition, the attention mechanism, normalization method, and hybrid anchor branch classification subnet are introduced to improve the overall detection performance. Our method achieves the current highest F1-score of 0.888 on the public dataset ICPR 2012. We also evaluated our method on the GZMH dataset released by our research team for the first time and reached the highest F1-score of 0.563, which is also better than multiple classic detection networks widely used at present. It confirmed the effectiveness and generalization of our method. The code will be available at: https://***/antifen/mitosis-nuclei-detection. Copyright © 2023, The Authors. All rights reserved.

关键词： Grading

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A Chinese Sentiment Analysis Model Incorporating Knowledge Graph and Deep Learning

A Chinese Sentiment Analysis Model Incorporating Knowledge G...

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2023 7th International Conference on Electrical, Mechanical and Computer Engineering (ICEMCE)

作者： Shengping Zhao Jinlong Chen Xingguo Qin School of Computer Science and Information Security Guilin University of Electronic Technology Guilin China School of Computer Science and Information Security Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic Technology Guilin Guangxi China

With the rapid growth of social media and e-commerce, users are generating large amounts of textual review data on these platforms. Analyzing and mining these comment data is important for governments, enterprises, and consumers to make decisions. Therefore, sentiment analysis, especially for Chinese comments, has become an area of wide interest in industry and academia. Aiming at the characteristics of Chinese online reviews, this paper applies the techniques of knowledge graph and deep learning around sentence-level sentiment analysis and designs a sentiment analysis model that integrates different information such as sentiment knowledge graph and serialized annotation in a deep learning model to improve the accuracy and effectiveness of sentiment analysis of Chinese online reviews. This is important for improving products and services, understanding user needs, and making more informed business and policy decisions.

关键词：

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Links Between HX-Groups and Hypergroups

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Algebra Colloquium 2021年第3期28卷 441-452页

作者： Irina Cristea Michal Novák Babatunde Oluwaseun Onasanya Centre for Information Technologies and Applied Mathematics University of Nova Gorica Slovenia Faculty of Electrical Engineering and Communication Brno University of Technology Czech Republic Key Laboratory of Intelligent Information Processing and Control of Chongqing Municipal Institutions of Higher Education Chongqing Three Gorges University Chongqing 404000China Department of Mathematics University of IbadanNigeria

The concept of an HX-group is an upgrade of the concept of a group,in which a new operation is defined on the family of non-empty subsets of a *** this new support set together with the new operation is a group,then we call it an *** the other hand,a hyperoperation is a mapping having the same codomain as the operation of an HX-group,i.e.,the family of non-empty subsets of the initial set,but a different domain-the set *** could be(and was indeed)a source of confusion,which is clarified in this ***,HX-groups naturally lead to constructions of *** links between these two algebraic concepts are presented,with the aim of reviving the old notion of an HX-group in the current research on algebraic *** of such existing links and one newly established link are also discussed.

关键词： HX-group hyperstructure theory Chinese hypergroupoid EL-hyperstructure power set

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TransView: Inside, Outside, and Across the Cropping View Boundaries

TransView: Inside, Outside, and Across the Cropping View Bou...

引用

International Conference on Computer Vision (ICCV)

作者： Zhiyu Pan Zhiguo Cao Kewei Wang Hao Lu Weicai Zhong Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Huazhong University of Science and Technology Huawei CBG

ISBN: (纸本)9781665428132

We show that relation modeling between visual elements matters in cropping view recommendation. Cropping view recommendation addresses the problem of image recomposition conditioned on the composition quality and the ranking of views (cropped sub-regions). This task is challenging because the visual difference is subtle when a visual element is reserved or removed. Existing methods represent visual elements by extracting region-based convolutional features inside and outside the cropping view boundaries, without probing a fundamental question: why some visual elements are of interest or of discard? In this work, we observe that the relation between different visual elements significantly affects their relative positions to the desired cropping view, and such relation can be characterized by the attraction inside/outside the cropping view boundaries and the repulsion across the boundaries. By instantiating a transformer-based solution that represents visual elements as visual words and that models the dependencies between visual words, we report not only state-of-the-art performance on public benchmarks, but also interesting visualizations that depict the attraction and repulsion between visual elements, which may shed light on what makes for effective cropping view recommendation.

关键词： Visualization Computer vision Computational modeling Benchmark testing Feature extraction Transformers Decoding

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