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Feature matching based on geometric constraints in weakly calibrated stereo views of curved scenes

Journal of Systems engineering and Electronics 2008年第3期19卷 562-570页

作者： Bian Houqin Su Jianbo Dept. of Automation Shanghai Jiaotong Univ. Shanghai 200240 P. R. China School of Computer & Information Engineering Shanghai Univ. of Electric Power Shanghai 200090 P. R. China

The identification of the correspondences of points of views is an important task. A new feature matching algorithm for weakly calibrated stereo images of curved scenes is proposed, based on mere geometric constraints. After initial correspondences are built via the epipolar constraint, many point-to-point image mappings called homographies are set up to predict the matching position for feature points. To refine the predictions and reject false correspondences, four schemes are proposed. Extensive experiments on simulated data as well as on real images of scenes of variant dept.s show that the proposed method is effective and robust.

关键词： feature correspondence,epipolar geometry fundamental matrix homography.

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Load Shedding automation System on Smart Meter Using Fuzzy Logic Method

Load Shedding Automation System on Smart Meter Using Fuzzy L...

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2021 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial automation, ICAMIMIA 2021

作者： Farid, Imam Wahyudi Priananda, Ciptian Weried Yuhansyah, Divan Andika Arifiani, Siska Hariadi, Ridho Rahman Priyadi, Ardyono Purnomo, Mauridhi Hery Institut Teknologi Sepuluh Nopember Dept. Electrical Automation Engineering Dept. Electrical Engineering Surabaya Indonesia Institut Teknologi Sepuluh Nopember Dept. Electrical Automation Engineering Surabaya Indonesia Institut Teknologi Sepuluh Nopember Dept. Informatics Engineering Surabaya Indonesia Institut Teknologi Sepuluh Nopember Dept. Electrical Engineering Surabaya Indonesia Institut Teknologi Sepuluh Nopember Dept. Computer Engineering Surabaya Indonesia

ISBN: (纸本)9781665499699

The need for electrical energy for the household sector has become a basic need. However, there are still people who complain about expensive electricity bills. In addition, the use of electricity is not recommended to exceed the power capacity which can cause a short circuit. Therefore, a tool is needed, namely a Smart Meter that can monitor the use of electrical energy and can perform load shedding automatically to reduce the occurrence of short circuits. The load shedding automation system uses one of the methods of artificial intelligence technology, namely by using Mamdani's Fuzzy Logic so that it can recognize patterns, classify/identify, predict, and optimize the use of electrical energy. Load shedding is carried out based on priority loads and non-priority loads. From testing the load shedding automation system which was carried out 5x with 6x load combination trials, it resulted that in the 1st to 4th experiments, Relay_Hidup3 output was obtained. To carry out the load shedding process, the average delay time is 2,302 seconds © 2021 IEEE.

关键词： Fuzzy logic

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3-D shape recovery across two views based on approximate geometric constraints 6

3-D shape recovery across two views based on approximate geo...

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6th International Conference on Signal Processing, ICSP 2002

作者： Wong, Hau-San Chung, Ronald Dept. of Computer Science City University of Hong Kong Kowloon Tong Hong Kong Dept. of Automation and Computer-Aided Engineering Chinese University of Hong Kong Shatin Hong Kong

ISBN: (纸本)0780374886

In this paper, we propose a new approach to object matching and shape reconstruction across two views. The approach relies on the topological relationship among the feature points and a crude rigidity constraint (epipolar condition) in carrying the object from the mnodel view to the scene view to a first good approximation. The correspondences are then refined by fitting an active contour model to the transferred feature points on the scene view, which automatically assumes the shape of the object on correct matching. Under the assumption of weak perspective projection, it could be shown that the establishment of such correct correspondences would result in the full determination of the relative dept.s of all the matched object points in 3-D space and thus recovery of the complete 3-D structure of the object. © 2002 IEEE.

关键词： Shape optimization

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Modified particle swarm optimization for pattern clustering

Modified particle swarm optimization for pattern clustering

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19th International Conference on Neural Information Processing, ICONIP 2012

作者： Swetha, K.P. Susheela Devi, V. Dept. Electrical Engineering Indian Institute of Science Bangalore 560012 India Dept. Computer Science and Automation Indian Institute of Science Bangalore 560012 India

ISBN: (纸本)9783642344862

Data clustering is a common technique for statistical data analysis, which is used in many fields, including machine learning and data mining. Clustering is grouping of a data set or more precisely, the partitioning of a data set into subsets (clusters), so that the data in each subset (ideally) share some common trait according to some defined distance measure. In this paper we present the genetically improved version of particle swarm optimization algorithm which is a population based heuristic search technique derived from the analysis of the particle swarm intelligence and the concepts of genetic algorithms (GA). The algorithm combines the concepts of PSO such as velocity and position update rules together with the concepts of GA such as selection, crossover and mutation. The performance of the above proposed algorithm is evaluated using some benchmark datasets from Machine Learning Repository. The performance of our method is better than k-means and PSO algorithm. © 2012 Springer-Verlag.

关键词： Genetic algorithms

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Simultaneous feature selection and clustering using particle swarm optimization

Simultaneous feature selection and clustering using particle...

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19th International Conference on Neural Information Processing, ICONIP 2012

ISBN: (纸本)9783642344749

Data clustering groups data so that data which are similar to each other are in the same group and data which are dissimilar to each other are in different groups. Since generally clustering is a subjective activity, it is possible to get different clusterings of the same data depending on the need. This paper attempts to find the best clustering of the data by first carrying out feature selection and using only the selected features, for clustering. A PSO (Particle Swarm Optimization)has been used for clustering but feature selection has also been carried out simultaneously. The performance of the above proposed algorithm is evaluated on some benchmark data sets. The experimental results shows the proposed methodology outperforms the previous approaches such as basic PSO and Kmeans for the clustering problem. © 2012 Springer-Verlag.

关键词： Feature Selection

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Kernels on attributed pointsets with applications

Kernels on attributed pointsets with applications

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21st Annual Conference on Neural Information Processing Systems, NIPS 2007

作者： Parsana, Mehul Bhattacharya, Sourangshu Bhattacharyya, Chiranjib Ramakrishnan, K.R. Dept. of Computer Science and Automation Indian Institute of Science Bangalore - 560012 India Dept. of Electrical Engineering Indian Institute of Science Bangalore - 560012 India

ISBN: (纸本)160560352X

This paper introduces kernels on attributed pointsets, which are sets of vectors embedded in an euclidean space. The embedding gives the notion of neighborhood, which is used to define positive semidefinite kernels on pointsets. Two novel kernels on neighborhoods are proposed, one evaluating the attribute similarity and the other evaluating shape similarity. Shape similarity function is motivated from spectral graph matching techniques. The kernels are tested on three real life applications: face recognition, photo album tagging, and shot annotation in video sequences, with encouraging results.

关键词： Face recognition

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Brain Stroke Detection from CT Images using Transfer Learning Method 13

Brain Stroke Detection from CT Images using Transfer Learnin...

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13th International Conference on Advanced computer Information Technologies, ACIT 2023

作者： Çinar, Necip Kaya, Buket Kaya, Mehmet Dicle University Department of Computer Engineering Diyabakir Turkey Firat University Department of Electronics and Automation Elaziǧ Turkey Firat University Dept. of Computer Engineering Elaziǧ Turkey

Recently, with the production of high-capacity computers, artificial intelligence methods have been used in many areas. In particular, in the field of health, artificial intelligence methods are used to detect diseases and determine the treatments to be applied. Deep learning methods, a sub-branch of artificial intelligence, show a high success in diagnosing many diseases thanks to its deep CNN networks. In this study, firstly, it was tried to determine which deep learning methods are more successful for the detection of brain stroke from computerized tomography images. This study is of great importance in terms of determining which deep learning architectures we will focus on in our future studies on brain stroke. In this study, brain stroke disease was detected from CT images by using the five most common used models in the field of image processing, one of the deep learning methods. The pre-trained ResNetl01, VGG19, EfficientNet-B0, MobileNet-V2 and GoogleNet models were run with the same dataset and same parameters. As a result, the EfficientNet-B0 architecture showed the highest performance with 97.93% accuracy. ResNetl01, VGG19, MobileNet-V2 and GoogleNet models showed 94.32%, 97.28%, 92.30% and 91.61% accuracy rates, respectively. With this study, it was concluded that the EfficientNet architecture is more suitable for the detection of brain stroke disease from CT images. © 2023 IEEE.

关键词： Diagnosis

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Approximate off-line receding horizon control of constrained nonlinear discrete-time systems: Smooth approximation of the control law

Approximate off-line receding horizon control of constrained...

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作者： Pin, Gilberto Filippo, Marco Pellegrino, Felice Andrea Fenu, Gianfranco Parisini, Thomas Danieli Automation S.p.A Italy Dept. of Electrical Electronic and Computer Engineering DEEI University of Trieste Italy

ISBN: (纸本)9781424474264

In this work, the off-line approximation of state-feedback nonlinear model predictive control laws by means of smooth functions of the state is addressed. The idea is to investigate how the approximation errors affect the stability of the closed-loop system, in order to derive suitable bounds which have to be fulfilled by the approximating function. This analysis allows to conveniently set up the characteristic parameters of some techniques such as Neural Networks which can be used to implement the control law, in order to render the system Input-to-State Practically Stable while satisfying, in addition, hard constraints on the trajectories;both the amount of data storage and the computational time result strongly reduced with respect to Nearest Neighbor or Set Membership approaches, which have been recently proposed to obtain effective off-line approximation of nonlinear MPC. The provided simulations confirm the validity of the method. © 2010 AACC.

关键词： State feedback

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Analysis of the PV Energy Potential in the Bulgarian Danube River Region between Ruse and Silistra 5

Analysis of the PV Energy Potential in the Bulgarian Danube ...

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5th IEEE International Conference on Communications, Information, Electronic and Energy Systems, CIEES 2024

作者： Gabrovska-Evstatieva, Katerina Stoyanov, Ivaylo Kaneva, Tsvetelina Valov, Nikolay Tsankov, Vladimir Evstatiev, Boris Mihailov, Nicolay University of Ruse Dept. of Computer Science Ruse Bulgaria University of Ruse Dept. of Electric Power Engineering Ruse Bulgaria University of Ruse Dept. of Computer Systems and Technologies Ruse Bulgaria University of Ruse Dept. of Automation and Electronics Ruse Bulgaria

ISBN: (纸本)9798350352863

The goal of the study is to assess and compare the photovoltaic energy potential in the central-eastern part of the Bulgarian Danube region between the cities of Ruse and Silistra. To achieve this the solar radiation and the temperature of the environment should be obtained and analyzed. The goal of the study is to assess and compare the photovoltaic energy potential in the central-eastern part of the Bulgarian Danube region between the cities of Ruse and Silistra. To achieve this the solar radiation and the temperature of the environment should be obtained and analyzed. The goal of the study is to assess and compare the photovoltaic energy potential in the central-eastern part of the Bulgarian Danube region between the cities of Ruse and Silistra. To achieve this the solar radiation and the temperature of the environment should be obtained and analyzed. © 2024 IEEE.

关键词： Solar irradiance

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Verification of logic control design using SIPN and model checking: Methods and case study

Verification of logic control design using SIPN and model ch...

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作者： Weng, Xiying Litz, Lothar Institute of Process Automation Dept. of Electrical and Computer Engineering University of Kaiserslautern PO 3049 D-67653 Kaiserslautem Germany

This paper deals with the verification of logic control system designs by signal interpreted Petri net (SIPN), which is a special extension of an ordinary Petri net (PN) by input and output signals. Such extensions provide more power for a specification. However, due to the extensions the basic Petri net analysis method is not strong enough to determine the properties. A model checking approach has been applied to the verification of an SIPN design. The requirements to be verified are expressed in temporal logic (TL). Via a model checking algorithm the validity of such requirements can be checked automatically in every possible input sequences. In an error case a sequence of states is calculated, which indicates a trace leading to the violation of the requirements. A case study has shown that this approach can effectively locate errors in the design process. © 2000 American Automatic Control Council.

关键词： Model checking

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