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31st International Conference on Computational Linguistics, COLING 2025

作者： Hou, Haowen Zeng, Peigen Ma, Fei Yu, Fei Richard Shenzhen China College of Computer Science and Software Engineering Shenzhen University Shenzhen China Shool of Information Technology Carleton University Canada

ISBN: (纸本)9798891761964

Visual Language Models (VLMs) have rapidly progressed with the recent success of large language models. However, there have been few attempts to incorporate efficient linear Recurrent Neural Networks (RNNs) architectures into VLMs. In this study, we introduce VisualRWKV, the first application of a linear RNN model to multimodal learning tasks, leveraging the pre-trained RWKV language model. We propose a data-dependent recurrence and sandwich prompts to enhance our modeling capabilities, along with a 2D image scanning mechanism to enrich the processing of visual sequences. Extensive experiments demonstrate that VisualRWKV achieves competitive performance compared to Transformer-based models like LLaVA-1.5 on various benchmarks. Compared to LLaVA-1.5, VisualRWKV has a speed advantage of 3.98 times and can save 54% of GPU memory when reaching an inference length of 24K tokens. To facilitate further research and analysis, we have made the checkpoints and the associated code publicly accessible at the following GitHub repository: https://***/howard-hou/VisualRWKV. © 2025 Association for Computational Linguistics.

关键词： Recurrent neural networks

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computer-aided Visual Modeling of Rice Leaf Growth Based on Machine Learning 23

Computer-aided Visual Modeling of Rice Leaf Growth Based on ...

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23rd International Conference on Soft Computing and Measurements, SCM 2020

作者： Yi, Wenlong Dai, Shiming Jiang, Yingzhao Yuan, Chao Yang, Le Jiangxi Agricultural University School of Software Engineering Nanchang China Jiangxi Agricultural University Shool of Computer and Information Engineering Nanchang China

ISBN: (纸本)9781728196923

Machine learning can abstract the complex plant growth and development into a high-dimensional feature space, and transform a complex biological process into a mathematical problem. In this paper, with the computer-aided modeling of rice leaf growth as an example, improving the accuracy of prediction models for external environmental factors of rice growth and parameters of leaf shape evolution is investigated. Two machine learning tools, SVR and CNN, are selected to compare and analyze the training and prediction errors of 709 collected sample data. The experimental results show that the prediction accuracy of CNN is about 2 times higher than that of SVR. However, the learning speed of SVR in solving small sample regression is 50 times higher than that of CNN. Finally, the obtained parameters for rice leaf growth shape prediction are subjected to geometric description using the B-spline function, and visual simulation is carried out by visual C++ programming language and OpenGL 3.2. Three-dimensional visual models of plant growth and development with an external growth environment are established using machine learning. The ideal plant morphology is obtained by adjusting external environmental factors reasonably through quantitative analysis. It provides an information tool for the transformation of traditional empirical agricultural production to precise mode. © 2020 IEEE.

关键词： Machine learning

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Decoupling of Direction and Length for Cumulative Step Size Adaptation 17

Decoupling of Direction and Length for Cumulative Step Size ...

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17th International Conference on Computational Intelligence and Security, CIS 2021

作者： Zhang, Shuo Li, Zhenhua Yang, Detian Wang, Shuo Cai, Xinye School of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China Shool of Information Technology and Engineering Tianjin University of Technology and Education Tianjin China

ISBN: (纸本)9781665494892

Covariance matrix adaptation evolution strategy (CMA-ES) is a successful evolutionary algorithm for continuous optimization. The cumulative step size adaptation (CSA) is the default method for adapting the step size in CMA-ES and achieves remarkable performance in practice. It follows the idea of exploiting the correlations between search directions in consecutive generations. In this paper, we investigate the effects of the update directions and the length in CSA. We find that sampling from uniform sphere distribution can yield comparative performance to the default setting, and normalizing the update direction in CSA does not hurt the performance. Further, the CSA with actual search direction cannot perform well, and the correlation between the default direction of CSA and the actual search direction is rather small. It indicates that CSA does not accumulate the actual search directions. We argue that the step size and the covariance matrix should be updated by decoupled search information, and accumulating the actual search direction results in inferior performance due to the same update direction in two evolution paths for the step size and covariance matrix updates. © 2021 IEEE.

关键词： Covariance matrix

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Exploitation on the shool Affairs Workflow System

Exploitation on the Shool Affairs Workflow System

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2010 International Conference on Mechanic Automation and Control engineering, MACE2010

作者： Zeng, Qiangcong Zhao, Xin Shool of Information Hunan University of Commerce Changsha China Shool of Computer and Electronic Engineering Hunan University of Commerce Changsha China

ISBN: (纸本)9781424477388

The thesis ,which refers contents such as strategies of exploitation,affairs of system,structure of system and the character of workflow technology,has stated the exploitation of a school affairs workflow system based on organization *** exploitation of organization driving workflow is an point upon which the thesis discoursed *** to the thesis it is a workflow exploitation way resulting from experience and is adapted to exploiting the workflow systems with a strong dependence to organization structure. ©2010 IEEE.

关键词： Organization driving shool affairs System structure Workflow

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Analysis of image stitching error based on scale invariant feature transform and random sample consensus 12

Analysis of image stitching error based on scale invariant f...

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12th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2015

作者： Shuang, Dou Cai, Hua Yang, Yong Tailin, Han Xue, Menghan School of Computer Engineering Changchun University of Science and Technology Changchun China College of Electronic and Information Engineer Changchun University of Science and Technology Changchun China Electronic Engineering Shool Beijing University of Posts and Telecommunications Changchun China

ISBN: (纸本)9781467376822

This article introduced the process of image stitching based on SIFT and RANSAC. It was pointed out that the reliability calculation of the RANSAC algorithm is based on an idealized assumption which does not hold. The false assumption will lead to the instability of image stitching results, especially in multi-map or panorama situations. To solve the problem, this paper presents a strategy to limit the range of randomly points selecting. Experiments show that the strategy can effectively reduce the effect caused by random errors, and obtain more stable image stitching result. © 2015 IEEE.

关键词： Random errors

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Association Rules Mining with Multiple Constraints

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Procedia engineering 2011年 15卷 1678-1683页

作者： Li Guang-yuan Cao Dan-yang Guo Jian-wei School of Computer and Communication Engineering University of Science&Technology Beijing Beijing China Shool of Computer and Information Engineering Guangxi Teachers Education University Nanning China

Association rules mining(ARM) is an important task in the field of data mining, mining frequent itemsets is a key step of many algorithms for ARM. In a very large dataset, rules generated may be very large, but some of them are useless to the users, to improve the effectiveness and efficiency of mining tasks, constraint-based mining enables users to concentrate on mining their interested association rules instead of the complete set of association rules. Most of previously proposed methods are mainly deal with a single constraint. In this paper, we present an algorithm for mining association rules with multiple constraints, the proposed algorithm simultaneously copes with two different kinds of constraints, it consists of three phases, first, the frequent 1-itemset are generated, second, we exploit the properties of the given constraints to prune search space or save constraint checking in the conditional databases. Third, for each itemset possible to satisfy the constraint, we generate its conditional database and perform the three phases in the conditional database recursively. Experimental results show that the proposed method outperform the revised FP-growth algorithm.

关键词： Data mining Association rules mining Constraints-based mining

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computer-aided Visual Modeling of Rice Leaf Growth Based on Machine Learning

Computer-aided Visual Modeling of Rice Leaf Growth Based on ...

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International Conference on Soft Computing and Measurements (SCM)

作者： Wenlong Yi Shiming Dai Yingzhao Jiang Chao Yuan Le Yang School of Software Engineering Jiangxi Agricultural University Nanchang China Shool of Computer and Information Engineering Jiangxi Agricultural University Nanchang China

ISBN: (数字)9781728196923

ISBN: (纸本)9781728196930

关键词： Biological system modeling Predictive models Computational modeling Machine learning Image color analysis Data models Training

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VisualRWKV: Exploring Recurrent Neural Networks for Visual Language Models

arXiv

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arXiv 2024年

关键词： Recurrent neural networks

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Software design of intelligent solar drying system for agricultural and sideline products

Software design of intelligent solar drying system for agric...

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International Conference on Control, Automation, Robotics and Vision (ICARCV)

作者： Sijie Ouyang Jianping Chen Qijun Xiao Shun Cheng Shool of Electronic Information & Mechanical Electrical Engineering Zhaoqing University Zhaoqing China School of Computer Science Zhaoqing University Zhaoqing China

ISBN: (纸本)9781479952007

Solar energy is renewable energy which can be used in the drying of agricultural and sideline products. The lower computer measurement and control subsystem is designed and the improved binary table lookup algorithm is designed to realize the tank water temperature detection. The main program flow is demonstrated, furthermore, the host computer monitoring subsystem is constructed, in which the system database and communication mechanism are designed, and the algorithm design of host computer communication module is demonstrated. The man-machine interface is quite friendly for the user. Using this solar dring system, some drying experiments for longan and red pepper are done. Experiments show that the drying system can run reliably, therefore, software design of the intelligent solar drying system is effective.

关键词： computers Temperature measurement Humidity Storage tanks Monitoring Artificial intelligence Temperature distribution

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Decoupling of Direction and Length for Cumulative Step Size Adaptation

Decoupling of Direction and Length for Cumulative Step Size ...

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International Conference on Computational Intelligence and Security

作者： Shuo Zhang Zhenhua Li Detian Yang Shuo Wang Xinye Cai School of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China Shool of Information Technology and Engineering Tianjin University of Technology and Education Tianjin China

ISBN: (纸本)9781665494908

关键词： Correlation Evolutionary computation Security Covariance matrices Optimization

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