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检索条件"主题词=inference algorithms"

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Transformer-based Multi-Target Tracking with Bayesian Perspective

Transformer-based Multi-Target Tracking with Bayesian Perspe...

引用

International Conference on Information Fusion

作者： Xinwei Wei Yiru Lin Linao Zhang Zhiyuan Zou Jianwei Wei Wei Yi School of Information and Communication Engineering University of Electronic Science and Technology of China

ISBN: (数字)9781737749769

ISBN: (纸本)9798350371420

The Bayesian inference has a two-step recursion structure, i.e., prediction and updating, which can be viewed as a dynamic reasoning process. Based on this elegant structure, various multi-target tracking (MTT) algorithms have been invented and successfully applied in many areas. On the other hand, Bayesian inference MTT algorithms are model-based methods that rely on models’ accuracy and first-order Markov assumption. In recent years, the MTT algorithms based on deep learning have received much attention due to their model-free property and the ability to learn from data, although they have issues such as over-fitting, generalization, etc. In this work, we propose a Transformer-based multi-target tracker whose architecture mimics the Bayesian inference, referred to as the Bayesian inference-based Transformer (BAIT) for MTT. To deal with the model mismatch issues, BAIT uses neural networks instead of the pre-assumed motion and observation models while retaining the excellent architecture of Bayesian inference. BAIT can recursively complete accurate predictions and updates via Transformer by refining the estimation of target states in a Bayesian inference-like manner. Thus, BAIT can be viewed as a combination of model-based and data-based methods. The simulation results show that, because of combining the advantages of Bayesian architecture with intelligent data association structure, BAIT is competitive in simple scenarios and achieves superior performance when the data association task becomes complicated.

关键词： Accuracy Tracking Heuristic algorithms Simulation Neural networks Transformers Prediction algorithms inference algorithms Bayes methods Resource management

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Coupling an expert system with industrial real-time processes

Coupling an expert system with industrial real-time processe...

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Annual Conference of Industrial Electronics Society

作者： N. Bogunovic R Bošković Institute Zagreb Croatia

A diagnostic real-time expert system, applied to an industrial chemical process, is used as a testbed for research on integration of symbolic and numeric computations in a unified framework. The algorithms reveal the precise role and desirable characteristics of synergism between statistical process control and the expert system. Inferencing on the process performance is founded on the consistent and continuous acquisition of the process parameters, statistical and mass balance calculations, heuristic rules processing, and history data reporting. The implementation status and runtime performance of the system are given.< >

关键词： Expert systems Real time systems Diagnostic expert systems Electrical equipment industry Chemical industry Computer industry Chemical processes System testing inference algorithms Process control

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Lightning Fast Matching Dependency Discovery with Desbordante

Lightning Fast Matching Dependency Discovery with Desbordant...

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Open Innovations Association (FRUCT), Conference of

作者： Alexey Shlyonskikh Michael Sinelnikov Daniil Nikolaev Yurii Litvinov George Chernishev Saint-Petersburg University Saint-Petersburg Russia

ISBN: (数字)9789526524627

ISBN: (纸本)9798331507411

Matching dependency is a generalization of the functional dependency concept, which allows users to apply custom similarity functions for matching individual attributes. Matching dependencies have a wide range of applications for solving various data quality problems, such as entity resolution, data deduplication, data integration, schema matching, and many more. However, their discovery is a very computationally intensive problem, which limits their practical *** this paper, we describe a number of optimization techniques for HyMD — currently the state-of-the-art algorithm for the discovery of matching dependencies. These optimizations belong to both technical and scientific domains. The most important of them are: 1) a new sampling technique, 2) a faster generalization lookup technique, and 3) an improved representation of a dependency. The first one aims to raise the efficiency of inference from record pairs, while the last two are designed to speed up lattice-related *** evaluate our optimizations, we implemented our version of HyMD in Desbordante, an open-source high-performance data profiler. Experiments demonstrated that they allow for a speedup of more than 40x over the state-of-the-art implementation on average, reaching a speedup greater than 170x in some ***, the improved version of HyMD is ready to use by anyone. It comes with bidirectional Python integration, which allows calling the C++ algorithm implementation from Python programs while allowing users to supply their custom matching functions.

关键词： Technological innovation Data integrity Memory management Lightning Data integration inference algorithms Maintenance Optimization Pattern matching Python

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Subspace clustering for hierarchical fuzzy system construction

Subspace clustering for hierarchical fuzzy system constructi...

引用

IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： A. Chong T.D. Gedeon Sch. of Inf. Technol. Murdoch Univ. WA Australia School of Information Technology Murdoch University Murdoch Western Australia

Hierarchical fuzzy systems are proposed to deal with the rule explosion problem of traditional fuzzy systems. The inference operations of the fuzzy systems are well established. The next step is to tackle the problem of finding subspaces for automated hierarchical fuzzy system construction. We propose a clustering technique designed specifically for this purpose. It is both theoretically and experimentally confirmed that the algorithm has reasonable accuracy and scalability.

关键词： Fuzzy systems Clustering algorithms Data mining Explosions Information technology Australia inference algorithms Scalability Neural networks Joining processes

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A new sequential Monte Carlo algorithm for distributed blind equalization

A new sequential Monte Carlo algorithm for distributed blind...

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IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

作者： Claudio J. Bordin Marcelo G. S. Bruno Instituto Tecnológico de Aeronáutica Sao Jose dos Campos Brazil

This article describes a new distributed blind equalization algorithm based on particle filters suitable for CDMA systems operating on frequency-selective channels. The proposed approach processes the signal received by multiple receivers in a non-centralized fashion, determining approximately optimal estimates (MAP) of the transmitted symbols, which minimizes the expected error rate. The described receiver structure dispenses with the need of a data fusion center, and is capable of operating either independently or in cooperation with other receivers. As we verified via numerical simulations, cooperative operation leads to a significant performance improvement, without substantially increasing the algorithmpsilas computational complexity.

关键词： Receivers Blind equalizers Particle filters Signal processing algorithms Approximation methods inference algorithms Multiaccess communication

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Deep Learning-based Method for Automatic Fruit Fly Detection and Counting

Deep Learning-based Method for Automatic Fruit Fly Detection...

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Computing (ICOCO), IEEE International Conference on

作者： Indah Desri Wahyuni Nabila Husna Shabrina Suputa Department of Computer Engineering Faculty of Engineering and Informatics Universitas Multimedia Nusantara Tangerang Indonesia Department of Plant Protection Faculty of Agriculture Universitas Gadjah Mada Yogyakarta Indonesia

ISBN: (数字)9798331530303

ISBN: (纸本)9798331530310

Fruit flies are a major threat faced by snake fruit farmers. Fruit flies can degrade the quality of snake fruits and reduce the overall yield. Traps stuffed with Methyl Eugenol are commonly placed across snake fruit plantations to attract fruit flies. Farmers then manually counted and reported the trapped fruit flies as part of their pest management strategies. However, manually counting trapped fruit flies is time-consuming, leading to unwillingness among farmers to perform this task. This study aims to develop an automated detection and counting system using deep-learning-based methods to address this issue. The proposed system was built on a modified YOLOv5 algorithm, achieving a precision of 0.944, recall of 0.947, and mAP of 0.946, with an object-counting time of only 50 ms. These results demonstrate that the proposed fruit-fly detection and counting system offers excellent performance with rapid detection times

关键词： YOLO Training Learning systems Deep learning Plantations Pest control inference algorithms Mobile applications Monitoring Testing

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Max-Margin Boltzmann Machines for Object Segmentation

Max-Margin Boltzmann Machines for Object Segmentation

引用

Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Jimei Yang Simon Sáfár Ming-Hsuan Yang University of California Merced

We present Max-Margin Boltzmann Machines (MMBMs) for object segmentation. MMBMs are essentially a class of Conditional Boltzmann Machines that model the joint distribution of hidden variables and output labels conditioned on input observations. In addition to image-to-label connections, we build direct image-to-hidden connections to facilitate global shape prediction, and thus derive a simple Iterated Conditional Modes algorithm for efficient maximum a posteriori inference. We formulate a max-margin objective function for discriminative training, and analyze the effects of different margin functions on learning. We evaluate MMBMs using three datasets against state-of-the-art methods to demonstrate the strength of the proposed algorithms.

关键词： Shape Training Object segmentation inference algorithms Joints Prediction algorithms Partitioning algorithms

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On the use of recurrent neuro-fuzzy networks for predictive control

On the use of recurrent neuro-fuzzy networks for predictive ...

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Conference of the North American Fuzzy Information Processing Society - NAFIPS

作者： A.R. Sadeghian J.D. Lavers Department of Math Physics & Computer Science Ryerson University Toronto ONT Canada Department of Electrical & Computer Engineering University of Toronto Toronto ONT Canada

This paper presents the application of recurrent neuro-fuzzy networks for the predictive control of nonlinear, multivariable, complex systems such as electric arc furnaces. The main objectives are to investigate the capability of adaptive neuro-fuzzy networks to predict the V-I characteristics of electric arc furnaces and to compare the performance of the proposed predictors with that of the feedforward neuro-fuzzy predictors. The novelties of this work are to propose the notion of approximate prediction and to implement it using a recurrent neuro-fuzzy structure suitable for long-term prediction. Successful implementations of recurrent neuro-fuzzy predictors are described and their performances are illustrated.

关键词： Fuzzy neural networks Predictive control Furnaces Adaptive systems inference algorithms Voltage fluctuations Neural networks Steel Recurrent neural networks Fuzzy logic

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An interval-valued fuzzy reasoning algorithm based on OWA operator

An interval-valued fuzzy reasoning algorithm based on OWA op...

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IEEE International Conference on Intelligent Computing and Intelligent Systems (ICIS)

作者： Qiansheng Zhang Shengyi Jiang Shihua Luo Haixiang Yao School of Information Science and Technology Guangdong University of Foreign Studies (GDUFS) Guangzhou China School of Information Management Jiangxi University of Finance and Economics Nanchang China

ISBN: (纸本)9781424447374;9781424447541

This paper presents a weighted interval-valued fuzzy (IvF) reasoning algorithm based on OWA operator for IvF inference system where interval-valued fuzzy set (IvFS) theory and IvF production rules with parameters are used for uncertain knowledge representation. The proposed algorithm can perform IvF matching between the fact and the antecedent portion of IvF rule by employing the weighted similarity measure. Finally, one numeric example illustrates that the proposed method is very flexible and simple.

关键词： Fuzzy reasoning Open wireless architecture In vitro fertilization inference algorithms Fuzzy set theory Fuzzy systems Production systems Knowledge representation Performance evaluation Weight measurement

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A multivariable fuzzy logic controller (MFLC) for a buck DC-DC converter

A multivariable fuzzy logic controller (MFLC) for a buck DC-...

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Annual IEEE Conference on Power Electronics Specialists (PESC)

作者： J.A. Asumadu E. Ho Electrical and Computer Engineering Department Western Michigan University USA

This paper describes the design and construction of a multivariable fuzzy controller (MFLC) for the control of a DC-DC buck converter. An off-the-shelf hardware-based MFLC system has been developed that is used to model the variable switching structure of the buck converter. The MFLC design criterion is based on the error in output voltage and the change of error in the output voltage as inputs of the controller, and the changes in the duty cycle ratio as output of the controller. The error and change of error are two membership functions bounded in the interval [0, 1]. The two inputs have two fuzzy subsets, negative fuzzy subset N and positive fuzzy subset P. The output is made up of fuzzy subsets of singletons. It will be shown that when the error and change of error have the same signs, the output moves away from a set point and therefore the same reasoning or rules can be used to change the output. The results will show that the MFLC technique provides robust control for nonlinear power electronics variable switching structure like the DC-DC buck converter.

关键词： Fuzzy logic DC-DC power converters Electric variables control Buck converters Sliding mode control Error correction Voltage control Power electronics Circuit topology inference algorithms

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