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A hierarchical correlation model for multi-model sentiment analysis on social media 12

A hierarchical correlation model for multi-model sentiment a...

引用

12th Chinese Conference on Computer Supported Cooperative Work and Social Computing, ChineseCSCW 2017

作者： Lin, Dazhen Li, Lingxiao Cao, Donglin Li, Shaozi Cognitive Science Department Xiamen University Xiamen China Fujian Key Laboratory of Brain-inspired Computing Technique and Applications Xiamen University Xiamen China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou China

ISBN: (纸本)9781450353526

We address the challenge of multi-modal sentiment analysis. To solve the problem of the sentiment correlations among different modalities, we propose a Multi-modal Correlation Model (MCM). In contrast to other methods, MCM considers the hierarchical sentiment correlations among modalities. Specifically, a probabilistic graphical model (PGM) is subsequently built upon the proposed MCM model, which considers the correlations and simultaneously preserves the classification ability of each modality. In order to compute the posterior probabilities of sentiments in PGM, we optimize the model by Maximum Likelihood Estimation. Experimental results show that MCM achieves accuracy of 84.2% and beats existing multi-modal methods with 1.2-4% improvement. Results demonstrate: 1) the sentiment correlations among modalities are hierarchical;2) the importance of the correlations for multi-modal sentiment analysis. © 2017 Association for Computing Machinery.

关键词： Sentiment analysis

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Image Dehazing Network Based on Multi-scale Feature Extraction 4th

Image Dehazing Network Based on Multi-scale Feature Extracti...

引用

4th International Conference on Smart Vehicular Technology, Transportation, Communication and Applications, VTCA 2021

作者： Feng, Ting Zhang, Fuquan Yu, Zhaochai Li, Zuoyong Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou350121 China College of Mathematics and Computer Science Fuzhou University Fuzhou350108 China

ISBN: (纸本)9789811640384

To remove image haze and make haze image scene clear, we proposed an image dehazing network based on multi-scale feature extraction (MSFNet) in this paper. The MSFNet first directly performs feature extraction on hazy images with three different resolutions to obtain fine feature maps and concatenates them with the rough feature maps extracted in the downsampling process for fusing and obtaining richer image information. Then, the fused feature maps are put into a network module composed of ResNeXt building blocks for network learning. Next, the feature maps extracted by upsampling are sequentially concatenated with the feature maps learned by the ResNeXt module for obtaining the residual image. Finally, the learned residual image is added to the input hazy image to obtain the image dehazing result. The experimental results on the SOTS dataset show that the MSFNet improves effectiveness of image dehazing. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Feature extraction

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Semantic Correspondence with Peripheral Position Coding 13

Semantic Correspondence with Peripheral Position Coding

引用

13th International Conference on information Technology in Medicine and Education, ITME 2023

作者： Chen, Jinjian Li, Zuoyong Lai, Taotao Xie, Huosheng College of Computer and Data Science Fuzhou University Fuzhou350108 China College of Computer and Control Engineering Minjiang University Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Fuzhou350121 China

ISBN: (纸本)9798350319156

Establishing dense correspondences between semantically similar images is a challenging task. Cost aggregation is a crucial step in finding correct dense correspondences, with the goal of optimizing the initial correlation map thereby removing the ambiguity of the correspondences. Current approaches use transformer architectures for cost aggregation, which lack local priors to adequately capture the local information contained in the correlation map. We propose to incorporate peripheral position coding into the transformer to explore the local information to obtain the matching set and call it the Peripheral Transformer Matcher (PTM). This coding technique partitions the overall receptive field of the self-attention mechanism into diverse peripheral regions, each with its own set of weights. By doing this, the proposed PTM gets a specific local prior by adding an inductive bias to the transformer models and making the initial correlation map less confusing. In addition, a local self-attention module is used to enhance the image features and obtain an enhanced initial correlation map. Comparisons of the experimental results with baselines on public datasets demonstrate the effectiveness of the proposed PTM. © 2023 IEEE.

关键词： Image enhancement

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Estimation of Motor Imagination Based on Consumer-Grade EEG Device 3rd

Estimation of Motor Imagination Based on Consumer-Grade EEG ...

引用

3rd International Conference on Machine Learning for Cyber Security, ML4CS 2020

作者： Luo, Zhenzhen Hu, Zhongyi Li, Zuoyong College of Computer and Artificial Intelligence Wenzhou University Wenzhou China Intelligent Information Systems Institute Wenzhou University Wenzhou China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou China

ISBN: (纸本)9783030624590

Nowadays, classifying electroencephalogram (EEG) signals based motor imagery tasks is extensively used to control brain-computer interface applications, as a communication bridge between humans and computers. In this paper, we propose signal-to-image transformation and feature extraction methods for the classification of motor imagery. Specifically, a continuous wavelet transform is applied to decompose EEG signals into five rhythms and generate time-frequency images. Then, a gray-level co-occurrence matrix is used to extract global texture features on time-frequency images. Finally, the SVM classification model is optimized by using a grid search algorithm to select optimal parameter pairs. To confirm the validity of the proposed methods, we experimented on self-collected data, which is obtained using a consumer-grade EEG device. The experimental result showed that this proposed method can achieve an acceptable classification accuracy of 90% for a two-class problem (left/right-hand motor imagery). © 2020, Springer Nature Switzerland AG.

关键词： Electroencephalography

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Chinese microblog rumor detection based on deep sequence context

Chinese microblog rumor detection based on deep sequence con...

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作者： Lin, Dazhen Ma, Ben Cao, Donglin Li, Shaozi Department of Cognitive Science Xiamen University Xiamen China Fujian Key Laboratory of Brain-inspired Computing Technique and Applications Xiamen University Xiamen China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou China

Rumor is one of the main problems in social media, which often shows deeply and rapidly undesirable affection on the society. Although many rumor detection models consider content features and social features, all of them are based on the word independence assumption, which lacks the sequence context. Thus, if we use some words that often appear in rumors, our posts will be recognized as a rumor. To solve this problem, we propose a deep sequence context model (DSCM) for Chinese microblog rumor detection. This model considers two important factors of rumors: falsity and influence. Firstly, to learn falsity, we abolish the word independence assumption and use long short-term memory (LSTM) units to capture bi-direction sequence context information in content. Secondly, to learn influence, we combine the deep sequence context information with social features to learn the connection between content and social features. In our experiment, our results show that our approach outperforms several state-of-the-art machine learning approaches, including term frequency and inverse document frequency (TFIDF), LSTM, and gated recurrent unit (GRU) in rumor detection. © 2018 John Wiley & Sons, Ltd.

关键词： Long short-term memory

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Dual-view Label and Feature Supervision Network for Semi-supervised Medical Image Segmentation 24

Dual-view Label and Feature Supervision Network for Semi-sup...

引用

7th International Conference on Signal processing and Machine Learning, SPML 2024

作者： Zhou, Zhen Li, Zuoyong Wang, Zhengyuan Teng, Shenghua Wang, Tao College of Electronic and Information Engineering Shandong University of Science and Technology Qingdao China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control School of Computer and Big Data Minjiang University Fuzhou China

ISBN: (纸本)9798400717192

Semi-supervised learning has garnered significant attention, particularly in medical image segmentation, owing to its capacity to leverage a large number of unlabeled data and a limited amount of labeled data to improve performance. However, most existing semi-supervised segmentation methods exhibit shortcomings in supervising unlabeled data, both in the label space due to potential noise in pseudo-labels, and the feature space due to indistinct class boundaries. To address the issues above, we propose Dual-view Label and Feature Supervision Network, termed DLFS-Net, to enhance label and feature supervision for unlabeled data. Our approach is based on a dual-view learning strategy that incorporates two modules: the Confidence Fusion Supervision Module (CFS) and the Dual-view Prototype Learning Module (DPL). Specifically, the CFS module generates weight matrices to integrate complementary information from two model outputs, producing more accurate pseudo-labels in the label space. The DPL module reduces intra-class variations in the feature space from two different views through prototype learning to generate clear class boundaries. Experiments on the LA and Pancreas-CT datasets demonstrate that our framework show solid gains (e.g.,1.76% Dice and 2.37% Jaccard improvement on Pancreas-CT dataset with 20% labeled data) compared with the state-of-the-art methods. © 2024 ACM.

关键词： Self-supervised learning

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Regression-based execution time prediction in hadoop environment

Regression-based execution time prediction in hadoop environ...

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International Conference on information Technology and Computer Application Engineering, ITCAE 2014

作者： Wu, Xiao Dong Zeng, Yu Zhu Zhao, C.T. Faculty of Mathematics and Computer Science Quanzhou Normal University China Fujian Provincial Key Laboratory of Data Intensive Computing China Key Laboratory of Intelligent Computing and Information Processing Fujian Province University China

ISBN: (纸本)9781138027176

Hadoop MapReduce has been proven an effective computing model to deal with big data for the last few years. However, one technical challenge facing this framework is how to predict the execution time of an individual job. In this paper, we propose a regression-based method to predict the execution times of Hadoop jobs. The proposed prediction method consists of three phases: learning data sampling, regression analysis and making prediction. Experimental results show that the predicted execution time obtained by our method is close to the actual execution time. © 2015 Taylor & Francis Group, London.

关键词： Regression analysis

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An Adaptive Multimeme Memetic Algorithm for the VLSI Standard Cell Placement Problem 16th

An Adaptive Multimeme Memetic Algorithm for the VLSI Standar...

引用

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： Chen, Xiongfeng Chen, Jianli Wang, Tao Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350108 China Center for Discrete Mathematics and Theoretical Computer Science Fuzhou University Fuzhou350108 China

ISBN: (纸本)9789813367562

Placement has a tremendous impact on the final performance of a VLSI chip, and the problem itself is a combinatorial optimization problem. Memetic algorithms with problem-specific designs can solve the problem with high quality solutions, but they are generally time-consuming. To address this issue, adopting an adaptive strategy has become a key way to reduce the runtime of a memetic algorithm. In this paper, we present an adaptive multimeme memetic algorithm (AMMA) for the VLSI standard cell placement problem. In accordance with the distinctive features of the solution space of the problem, we propose a set of adaptive strategies to greatly improve the runtime efficiency. The main novelty of the proposed strategy lies in its constructing of crossover multimeme and the acceptance criteria of placement candidates. The experimental results and comparisons on Peko suite3 and ISPD04 benchmark circuits verified the efficacy and efficiency of the proposed adaptive strategies. Compared to the memetic algorithm without these main adaptive strategies, the AMMA reduces the runtime by around 32.58% on average. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021.

关键词： Combinatorial optimization

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Concentration control of SMB system in parameter space of region velocity based on adjusted fuzzy control

Concentration control of SMB system in parameter space of re...

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作者： Xie, Chao-Fan Xu, Lu-Xiong Zhang, Fuquan Department of Electrical Engineering I-Shou University Kaohsiung Taiwan Electronic Information and Engineering Institute Fuqing Branch of Fujian Normal University China Key Laboratory of Nondestructive Testing Fuqing Branch of Fujian Normal University China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Fuzhou China

Because of high efficiency and cleanness, the simulated moving bed (SMB) is the most important technology in chromatographic separation. SMB system, which contains several sectors of flow rate, the switching time of valves and many other possible influencing variables, is complex, highly sensitive and difficult to control. This paper proposes adjusted fuzzy control;the adjusted fuzzy controller is applied to the SMB system to control the separation concentration by establishing a variable direction correction formula. Compared with the traditional fuzzy controller, the adjusted fuzzy controller does not need to analyze the dynamic direction of the control force in advance, moreover, the control accuracy is high and the fluctuation is small for SMB system. © 2020 - IOS Press and the authors. All rights reserved.

关键词： Fuzzy control

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White blood cell segmentation based on dual path network and channel attention 7

White blood cell segmentation based on dual path network and...

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7th International Conference on information Science and control Engineering, ICISCE 2020

作者： Lu, Yan Cao, Xinrong Li, Zuoyong Wang, Tao Minjiang University Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Fuzhou350121 China Fuzhou Digital Healthcare Industry Technology Innovation Center Fuzhou350121 China

ISBN: (纸本)9781728164069

White blood cell (WBC, leukocyte) in blood smear image plays a crucial role in the diagnosis of many blood diseases. WBC segmentation is an important preprocessing step in blood disease diagnosis. However, due to some factors such as different dying technologies and different WBC appearances, WBC segmentation is still challenging. To improve accuracy of WBC segmentation, we propose an end-to-end WBC segmentation network. Specifically, we first introduce Dual Path Network (DPN) as a context-aware feature encoder to extract multi-scale image features. Then, we use a channel attention module to capture the interdependencies between channel maps, and further enhance feature representation capability of the proposed network. Finally, we reconstruct WBC feature maps by a feature decoder, and use skip connections to reduce image information loss. Experimental results on three datasets show that the proposed method obtains higher segmentation accuracy than the other methods. © 2020 IEEE.

关键词： Image segmentation

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