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检索条件"机构=Tianjin Intelligent Computing and Software New Technology Key Laboratory"

共 168 条记录，以下是71-80 订阅

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Research on Character Vector Generation Method Based on Words and Context

Research on Character Vector Generation Method Based on Word...

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作者： Yiying Wang Hongyun Ning Tianjin Key Laboratory of Intelligence Computing &New Software Technology Tianjin University of Technology Tianjin Key Laboratory of Intelligence Computing & New Software Technology Tianjin University of Technology

In order to solve the problem of character information limitation and the neglect of polysemy,a character vector generation method based on words and context is *** of all,introduce the concept of context *** the fact that the same word has different meanings in different contexts,some even have the opposite meanings,therefore,to correctly understand the meaning of Chinese words,we must fully consider the context in which it is *** sentence in which the character or word is located is expressed in the form of a vector called context ***,construct the polysemous storage of *** the importance of context and the polysemy of words,this paper expands the expression of the original word vector,and adds a context linked list for each word *** multiple semantics of words are stored in multiple context vectors in the linked list,so as to solve the polysemy problem of ***,a character vector generation method based on words and context is *** target character vector is calculated by using the word vectors of all words containing the target character and its context ***,attention mechanism is *** calculating,the current character context and the word context are compared,according to the character and word context similarity to distribute weights,so that the words with more similar context make greater contribution to the generation of the character *** method not only add the word information to the character,but also distinguishes different semantics according to the context of the character,and makes all words participate in the calculation of the character vector according to different *** experiment uses the character vector evaluation method based on external tasks,taking the news title similarity task as an example,comparing the performance of the traditional CBOW method and the new words and context based character generation method in the t

关键词： CBOW character vector context Attention mechanism

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On-line Detection and Analysis of Alloy Steel Elements Based on the LIBS technology and Random Forest Regression

On-line Detection and Analysis of Alloy Steel Elements Based...

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第37届中国控制会议

作者： Yang Jixuan Zhang Qin Yang Peng Sun Junqing Tianjin Key Laboratory of Intelligent Computing and Novel Software Technology Tianjin University of Technology

The Laser Induced Breakdown Spectroscopy（LIBS） technology can be used to detect the elements in the alloy steel in real time. Quantitative analysis method of the traditional LIBS technology mainly has the calibration method and calibration free method, but there are two shortcomings: low prediction accuracy and over fitting. Random Forest Regression（RFR） algorithm can be used for classification and regression, can effectively avoid "overfitting" phenomenon. Therefore, in this paper, we combine the random forest regression algorithm with laser induced breakdown spectroscopy applied to the detection of the concentration of alloy steel elements in the metallurgy industry. At the same time, compared with partial least squares method based on the LIBS, the results show that the random forest algorithm combined with the LIBS technology has the higher prediction accuracy, lower root mean square error and better robustness.

关键词： LIBS quantitative analysis RFR PLS root mean square error

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Hybrid Variational Autoencoder for Collaborative Filtering 25

Hybrid Variational Autoencoder for Collaborative Filtering

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25th IEEE International Conference on Computer Supported Cooperative Work in Design, CSCWD 2022

作者： Liu, Jinxin Xiao, Yingyuan Zhu, Ke Zheng, Wenguang Hsu, Ching-Hsien Tianjin University of Technology Engineering Research Center of Learning-Based Intelligent System Ministry of Education Tianjin China Tianjin University of Technology Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin China Asia University Department of Computer Science and Information Engineering Taichung Taiwan

ISBN: (纸本)9781665405270

In recent years, Variational AutoEncoder (VAE) based methods have made many important achievements in the field of collaborative filtering recommendation system. VAE is a kind of Bayesian model which combines latent variable model with variational inference, but its optimization is often troubled by posterior collapse. By comparing the optimization process of VAE and ordinary autoencoder, we observe that the mismatch between poorly optimized encoder and decoder with too strong characterization capabilities makes it difficult to learn the mapping from the data manifold to the parameterized graph. Since the learning of a posteriori network corresponds to the encoder, we think that the problem of a posteriori collapse can be alleviated by balancing the encoder and decoder better. Therefore, we proposed Hy-VAE, which combines conventional VAE with deterministic autoencoder, and has the advantages of both VAE and deterministic autoencoder. Experiments on three real-world recommendation data sets show that our method alleviates the posterior crash problem in VAE and improves the recommendation performance. © 2022 IEEE.

关键词： Collaborative filtering

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Deep User and Item Inter-matching Network for CTR Prediction 28th

Deep User and Item Inter-matching Network for CTR Predicti...

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28th International Conference on Database Systems for Advanced Applications, DASFAA 2023

作者： Yuan, Zhiyang Xiao, Yingyuan Yang, Peilin Hao, Qingbo Wang, Hongya Engineering Research Center of Learning-Based Intelligent System Ministry of Education Tianjin University of Technology Tianjin300384 China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology Tianjin300384 China College of Computer Science and Engineering Donghua University Shanghai China

ISBN: (纸本)9783031306716

CTR prediction plays an important role in increasing company revenue and user experience, and many efforts start with historical behavior to uncover user interest. There are two main problems with previous works: (1) When most previous works mined interests from users’ historical behaviors, they only focus on implicit or explicit interests. (2) When most previous works mined user interests through the relationship between target users and similar users, the representation of target users was not rich and accurate enough, resulting in less accurate item recommendations. Therefore the Deep User and Item Inter-Matching Network (DUIIN) is proposed in this paper to solve the above problems. First, we design Item-to-Item Network (IIN), using two different sub-networks Evolving Interest Network (EIN) and Feature Interaction Network (FIN) to mine the hidden interests and explicit interests shown by users’ historical behaviors, respectively. Then the User-to-User Network (UUN) is designed to mine user interests through the relationship between target users and similar users after representing the target users more accurately and richly. The experimental results show that the DUIIN model proposed in this paper performs better than other state-of-the-art models. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Forecasting

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Vector-valued Chan-Vese model driven by local histogram for texture segmentation

Vector-valued Chan-Vese model driven by local histogram for ...

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IEEE International Conference on Image Processing

作者： Yuanquan Wang Yue Xiong Liping Lv Hua Zhang Zuoliang Cao Degan Zhang Tianjin Key Laboratory of Intelligent Computing and Novel Software Technology Tianjin University of Technology Tianjin China

The Chan-Vese model is one of the most popular region-based active contours, and its vector-valued extension is also powerful for multichannel images. Very recently, the histogram is introduced into the Chan-Vese model due to the effectiveness of histogram to model region information. Motivated by the fact that the histogram is also a powerful tool to characterize texture, it is introduced into the vector-valued Chan-Vese model for texture segmentation in this work. In order to determine an optimal number of bins in the histogram, a Bayesian method is adopted. Experiments are conducted and the results show that the proposed strategy is effective for texture segmentation.

关键词： Histograms Active contours Image segmentation Image edge detection Computational modeling Filter bank Computer vision

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An Edge Preserving Gradient Vector Flow for Active Contours

An Edge Preserving Gradient Vector Flow for Active Contours

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Congress on Image and Signal Processing, CISP

作者： Xiao Jia Yuanquan Wang Tianjin Key Laboratory of Intelligent Computing and Novel Software Technology Tianjin University of Technology Tianjin China

Snakes or active contours are widely used in the fields of computer vision and image processing. Gradient vector flow (GVF) is an effective external force for active contours, but it is based on isotropic diffusion and doesn't take the image structure into account. In this study, a novel external force for active contours, named edge preserving gradient vector flow is proposed for active contours. The gradient information of the image is used in the proposed model. This proposed model has been assessed on different images; experimental results show that the new model provides much better results than GVF snake in terms of noise robustness, weak edge preserving, and concavity convergence.

关键词： Active contours Convergence Force control Computer vision Shape control Image processing Noise robustness Image segmentation Solid modeling Weight control

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Research on Green Vehicle Scheduling Problem of Free Picking up and Delivering Customers for Airlines Ticketing Company

Research on Green Vehicle Scheduling Problem of Free Picking...

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The 2nd National Conference on Information technology and Computer Science(CITCS 2015)

作者： Hainan Zhao Meiling Feng Junqing Sun Zhijing Gou Tianjin Key Laboratory of Intelligent Computing and Novel Software Technique Tianjin University of Technology

In this paper, the vehicle scheduling and routing problem of airline ticketing companies which provide free services of picking customers up and delivering them to airports is studied. Taking the time window constraints, customer satisfaction and time-dependent factors into consideration, this paper presents the mathematical model which take minimizing vehicle use cost and carbon emission as its objectives. According to the characteristics of the problem, a hybrid algorithm, which combines heuristic and tabu search algorithms, is designed to solve the model. Then, a simulated numerical case is employed to verify the validity of the mathematical model and the hybrid algorithm proposed in this paper. The simulating experiment about the numerical case show that by the model and the hybrid algorithm a vehicle scheduling and routing plan can be found with significant reduction in carbon emission and without clear increase of the total vehicle operational cost compared to the plan by the traditional approach.

关键词： Vehicle Routing ProblemAirport Pickup ServiceGreen RoutesTabu Search AlgorithmCustomer Satisfaction

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On-line Detection and Analysis of Alloy Steel Elements Based on the LIBS technology and Random Forest Regression

On-line Detection and Analysis of Alloy Steel Elements Based...

引用

Chinese Control Conference (CCC)

作者： Yang Jixuan Zhang Qin Yang Peng Sun Junqing Tianjin Key Laboratory of Intelligent Computing and Novel Software Technology Tianjin University of Technology Tianjin China

The Laser Induced Breakdown Spectroscopy (LIBS) technology can be used to detect the elements in the alloy steel in real time. Quantitative analysis method of the traditional LIBS technology mainly has the calibration method and calibration free method, but there are two shortcomings: low prediction accuracy and over fitting. Random Forest Regression (RFR) algorithm can be used for classification and regression, can effectively avoid “overfitting” phenomenon. Therefore, in this paper, we combine the random forest regression algorithm with laser induced breakdown spectroscopy applied to the detection of the concentration of alloy steel elements in the metallurgy industry. At the same time, compared with partial least squares method based on the LIBS, the results show that the random forest algorithm combined with the LIBS technology has the higher prediction accuracy, lower root mean square error and better robustness.

关键词： Forestry Steel Regression tree analysis Predictive models Prediction algorithms Vegetation

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Optical Flow with Harmonic Constraint and Oriented Smoothness

Optical Flow with Harmonic Constraint and Oriented Smoothnes...

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International Conference on Image and Graphics (ICIG)

作者： Jie Zhao Yuanquan Wang Huaibin Wang Tianjin Key Laboratory of Intelligent Computing and Novel Software Technology Tianjin University of Technology Tianjin China

Computation of the optical flow from a sequence of images remains open in the community of computer vision. Two classical models for this problem are the global smoothness algorithm proposed by Horn-Schunck and the oriented smoothness algorithm by Nagel and Enkelmann. In order to increase the accuracy of motion discontinuity, we propose a new optical flow model which incorporates the harmonic smoothness constraint borrowed from the harmonic gradient vector flow (HGVF) model into the oriented smoothness constraint. In particular, we combine the curl term of the harmonic constraint with the oriented smoothness to control the direction of the displacement vectors together and introduce two spatially varying weighting functions to control the above-mentioned two terms. The benefit of the suggested strategies is illustrated qualitatively on the synthetical image and quantitatively on the Middlebury optical flow benchmark. Compared with the classical Horn-Schunck and Nagel-Enkelmann methods, this method can provide more accurate estimation of optical flow around motion discontinuities.

关键词： Computer vision Image motion analysis Optical imaging Harmonic analysis Brightness Equations Adaptive optics

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Learning with only multiple instance positive bags

Learning with only multiple instance positive bags

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2016 International Joint Conference on Neural Networks, IJCNN 2016

作者： Wang, Zhigang Zhao, Zengshun Zhang, Changshui Computer and Communication Engineering School Tianjin University of Technology Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology China Key Laboratory of Computer Vision and System Tianjin University of Technology Ministry of Education China College of Electronics Communication and Physics Shandong University of Science and Technology China Automation Department Tsinghua University State Key Laboratory of Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and Technology China

ISBN: (纸本)9781509006199

In traditional multiple instance learning (MIL), both positive and negative bags are required to learn a prediction function. However, a high human cost is needed to know the label of each bag - positive or negative. Only positive bags contain our focus (positive instances) while negative bags consist of noise or background (negative instances). So we do not expect to spend too much to label the negative bags. Contrary to our expectation, nearly all existing MIL methods require enough negative bags besides positive ones. In this paper we propose an algorithm called 'Positive Multiple Instance' (PMI), which learns a classifier given only a set of positive bags. So the annotation of negative bags becomes unnecessary in our method. PMI is constructed based on the assumption that the unknown positive instances in positive bags be similar each other and constitute one compact cluster in feature space and the negative instances locate outside this cluster. The experimental results demonstrate that PMI achieves the performances close to or a little worse than those of the traditional MIL algorithms on benchmark and real data sets. However, the number of training bags in PMI is reduced significantly compared with traditional MIL algorithms. © 2016 IEEE.

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