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Engineering Applications of Neural Networks 1

引用

丛书名： IFIP Advances in Information and Communication Technology

1000年

作者： Lazaros Iliadis Chrisina Jayne

ISBN: (数字)9783642239571

ISBN: (纸本)9783642239564;9783642269547

the two-volume set IFIP AICT 363 and 364 constitutes the refereed proceedings of the 12th international conference on Engineering Applications of Neural Networks, EANN 2011, and the 7th IFIP WG 12.5 international conference, AIAI 2011, held jointly in Corfu, Greece, in September 2011. the 52 revised full papers and 28 revised short papers presented together with 31 workshop papers were carefully reviewed and selected from 150 submissions. the first volume includes the papers that were accepted for presentation at the EANN 2011 conference. they are organized in topical sections on computer vision and robotics, self organizing maps, classification/pattern recognition, financial and management applications of AI, fuzzy systems, support vector machines, learning and novel algorithms, reinforcement and radial basis function ANN, machine learning, evolutionary genetic algorithms optimization, Web applications of ANN, spiking ANN, feature extraction minimization, medical applications of AI, environmental and earth applications of AI, multi layer ANN, and bioinformatics. the volume also contains the accepted papers from the Workshop on Applications of Soft computing to Telecommunication (ASCOTE 2011), the Workshop on Computational Intelligence Applications in Bioinformatics (CIAB 2011), and the Second Workshop on Informatics and Intelligent Systems Applications for Quality of Life Information Services (ISQLIS 2011).

关键词： Computation by Abstract Devices pattern recognition Artificial Intelligence Simulation and Modeling Biometrics User Interfaces and Human Computer Interaction

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Image and Graphics 1

引用

丛书名： Lecture Notes in Computer Science

1000年

作者： Huchuan Lu Risheng Liu Wanli Ouyang Hui Huang Jiwen Lu Jing Dong Min Xu

ISBN: (数字)9783031463051

ISBN: (纸本)9783031463044

the five-volume set LNCS 14355, 14356, 14357, 14358 and 14359 constitutes the refereed proceedings of the 12th international conference on Image and Graphics, ICIG 2023, held in Nanjing, China, during September 22–24, 2023.;the 166 papers presented in the proceedings set were carefully reviewed and selected from 409 submissions. they were organized in topical sections as follows: computer vision and pattern recognition; computer graphics and visualization; compression, transmission, retrieval; artificial intelligence; biological and medical image processing; color and multispectral processing; computational imaging; multi-view and stereoscopic processing; multimedia security; surveillance and remote sensing, and virtual reality.;the ICIG 2023 is a biennial conference that focuses on innovative technologies of image, video and graphics processing and fostering innovation, entrepreneurship, and networking. It will feature world-classplenary speakers, exhibits, and high-quality peer reviewed oral and poster presentations.

关键词： Image Processing and Computer Vision Artificial Intelligence pattern recognition Computer Systems Organization and Communication Networks

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Learning to Optimize Quantum Neural Networks Without Gradients 4

Learning to Optimize Quantum Neural Networks Without Gradien...

引用

4th IEEE international conference on Quantum computing and Engineering, QCE 2023

作者： Kulshrestha, Ankit Liu, Xiaoyuan Ushijima-Mwesigwa, Hayato Safro, Ilya Newark United States Fujitsu Research of America Sunnyvale United States

ISBN: (纸本)9798350343236

Quantum Machine Learning is an emerging sub-field in machine learning where one of the goals is to perform pattern recognition tasks by encoding data into quantum states. this extension from classical to quantum domain has been made possible due to the development of hybrid quantum-classical algorithms that allow a parameterized quantum circuit to be optimized using gradient based algorithms that run on a classical computer. the similarities in training of these hybrid algorithms and classical neural networks has further led to the development of Quantum Neural Networks (QNNs). However, in the current training regime for QNNs, the gradients w.r. t objective function have to be computed on the quantum device. this computation is highly non-scalable and is affected by hardware and sampling noise present in the current generation of quantum hardware. In this paper, we propose a training algorithm that does not rely on gradient information. Specifically, we introduce a novel meta-optimization algorithm that trains a meta-optimizer network to output parameters for the quantum circuit such that the objective function is minimized. We empirically and theoretically show that we achieve a better quality minima in fewer circuit evaluations than existing gradient based algorithms on different datasets. © 2023 IEEE.

关键词： pattern recognition

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Image and Graphics 1

引用

丛书名： Lecture Notes in Computer Science

1000年

作者： Huchuan Lu Risheng Liu Wanli Ouyang Hui Huang Jiwen Lu Jing Dong Min Xu

ISBN: (数字)9783031463143

ISBN: (纸本)9783031463136

关键词： Image Processing and Computer Vision Artificial Intelligence pattern recognition Computer Systems Organization and Communication Networks

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Image and Graphics 1

引用

丛书名： Lecture Notes in Computer Science

1000年

作者： Huchuan Lu Risheng Liu Wanli Ouyang Hui Huang Jiwen Lu Jing Dong Min Xu

ISBN: (数字)9783031463112

ISBN: (纸本)9783031463105

关键词： Image Processing and Computer Vision Artificial Intelligence pattern recognition Computer Systems Organization and Communication Networks

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Motion estimation using invariance under group transformations

Motion estimation using invariance under group transformatio...

引用

international conference on pattern recognition

作者： B. Duc Signal Processing Laboratory Swiss Federal Institute of Technology Lausanne Switzerland

this paper describes a spatiotemporal framework for motion estimation, based on a fully parametric motion model. the model type defines a group of transformations. the motion estimation consists in finding a subgroup ... 详细信息

关键词： Motion estimation Image sequences Optical computing Spatiotemporal phenomena Image motion analysis Signal processing algorithms Parameter estimation Signal processing Laboratories Motion analysis

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Rendering Optimization of Massive Map Annotation Point Data Based on Multi Strategy Fusion 12

Rendering Optimization of Massive Map Annotation Point Data ...

引用

12th international conference of Information and Communication Technology, ICTech 2023

作者： Wei, Zhijie Zhou, Xiaolei Xing, Wentai Bao, Changlin Zhou, Cheng Cao, Ruipu Shenyang Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China Qinghai Academy of Building Materials Science Xining China Suzhou Jiaoke Group Co. Ltd Nanjing China

ISBN: (纸本)9798350332919

Aiming at the problems of poor visualization effect and system lag delay caused by the rendering of massive map label points, an optimization strategy combining visual optimization technology and point aggregation algorithm is proposed, and it is officially put into use in a city and town pavement collapse monitoring visualization platform. Compared with the traditional annotation point optimization scheme, firstly, the annotation point classification processing according to the specific business scenario, asynchronous traversal of data combined with documentFragment and other optimization technologies, combined with the K-D tree-based Grid-Distance-based Clustering, by comparing the performance report detected by Google Lighthouse, the performance indicators in the page display are improved by about 26%. At the same time, in terms of optimization effect, the number of callout points rendered on the page is controlled, so that the number of reflow redraws caused by page rendering is further reduced. © 2023 IEEE.

关键词： Visualization

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Power Distribution Network Fault Recovery Based on Improved DQN Algorithm 12

Power Distribution Network Fault Recovery Based on Improved ...

引用

12th international conference of Information and Communication Technology, ICTech 2023

作者： Li, Aixin Han, Bo Shenyang Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9798350332919

When a branch fault occurs in the power distribution network, what kind of algorithm can be used to safely, quickly and accurately eliminate the fault and restore the power distribution network to the previous state is an urgent problem to be solved. Due to the diversity and complexity of the power distribution network topology, as well as the sparseness and inaccessibility of fault data, the processing of power distribution network fault recovery will be greatly affected. In order to solve various problems in power distribution network fault recovery, by combining the characteristics of reinforcement learning, such as autonomous learning and running without training samples, and the good data fit of neural network, a power distribution network fault based on DQN (Deep Q-Network) is proposed. the algorithm has been restored and some improvements have been made to the experience replay and reward mechanism in the algorithm, and a significant improvement has been achieved. through the simulation experiments of fault recovery of power distribution networks with different structures, the results show that the algorithm can effectively realize the recovery processing function of the faulty branch. © 2023 IEEE.

关键词： Electric power distribution

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Image and Graphics 1

引用

丛书名： Lecture Notes in Computer Science

1000年

作者： Huchuan Lu Risheng Liu Wanli Ouyang Hui Huang Jiwen Lu Jing Dong Min Xu

ISBN: (数字)9783031463082

ISBN: (纸本)9783031463075

the five-volume set LNCS 14355, 14356, 14357, 14358 and 14359 constitutes the refereed proceedings of the 12th international conference on Image and Graphics, ICIG 2023, held in Nanjing, China, during September 22–24, 2023.;the 166 papers presented in the proceedings set were carefully reviewed and selected from 409 submissions. they were organized in topical sections as follows: computer vision and pattern recognition; computer graphics and visualization; compression, transmission, retrieval; artificial intelligence; biological and medical image processing; color and multispectral processing; computational imaging; multi-view and stereoscopic processing; multimedia security; surveillance and remote sensing, and virtual reality.;the ICIG 2023 is a biennial conference that focuses on innovative technologies of image, video and graphics processing and fostering innovation, entrepreneurship, and networking. It will feature world-classplenary speakers, exhibits, and high quality peer reviewed oral and poster presentations.

关键词： Image Processing and Computer Vision Artificial Intelligence pattern recognition Computer Systems Organization and Communication Networks

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Efficient computation of 3D moments

Efficient computation of 3D moments

引用

international conference on pattern recognition

作者： BingCheng Li Song De Ma National Pattern Recognition Laboratory Institute of Automation Chinese Academy and Sciences Beijing China

ISBN: (纸本)0818662654

In this paper, we proposed a linear-transform-based method to compute 3D moments. Instead of computing the conventional moments directly, we compute the so-called LT moments which are related with the conventional moments by three linear transforms. By choosing appropriately these transforms, it is shown that the computational complexity can be considerably reduced.

关键词： Computational complexity IIR filters Filtering Vectors pattern recognition Laboratories Automation Instruction sets Polynomials

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