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检索条件"任意字段=2021 10th International Conference on Computing and Pattern Recognition"

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10th international conference on theory and Practice of Natural computing, TPNC 2021

10th International Conference on Theory and Practice of Natu...

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10th international conference on theory and Practice of Natural computing, TPNC 2021

ISBN: (纸本)9783030904241

the proceedings contain 9 papers. the special focus in this conference is on theory and Practice of Natural computing. the topics include: Dynamic Heuristic Set Selection for Cross-Domain Selection Hyper-heuristics;on the Transfer Learning of Genetic Programming Classification Algorithms;on Injecting Entropy-Like Features into Deep Neural Networks for Content Relevance Assessment;ABCD: Analogy-Based Controllable Data Augmentation;MOEA/D with Adaptative Number of Weight Vectors;parallel Asynchronous Memetic Optimization for Freeform Optical Design;ant-Based Generation Constructive Hyper-heuristics for the Movie Scene Scheduling Problem.

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Learning Non-Markovian Constraints for Handwriting recognition 13

Learning Non-Markovian Constraints for Handwriting Recogniti...

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13th IAPR international conference on Document Analysis and recognition (ICDAR)

作者： Kakisako, Ryosuke Uchida, Seiichi Volkmar, Frinken Kyushu Univ Fukuoka 8190395 Japan

ISBN: (纸本)9781479918058

Recently, the horizon of dynamic time warping (DTW) for matching two sequential patterns has been extended to deal with non-Markovian constraints. the non-Markovian constraints regulate the matching in a wider scale, whereas Markovian constraints regulate the matching only locally. the global optimization of the non-Markovian DTW is proved to be solvable in polynomial time by a graph cut algorithm. the main contribution of this paper is to reveal what is the best constraint for handwriting recognition by using the non-Markovian DTW. the result showed that the best constraint is not a Markovian but a totally non-Markovian constraint that regulates the matching between very distant points;that is, it was proved that the conventional Markovian DTW has a clear limitation and the non-Markovian DTW should be more focused in future research.

关键词： Markov processes computational complexity graph theory handwriting recognition learning (artificial intelligence) dynamic time warping horizon graph cut algorithm nonMarkovian DTW horizon nonMarkovian constraint learning polynomial time solvability sequential pattern matching Accuracy Decoding Optical computing handwriting recognition Optical computing Markov chain Graph theory DECODING complexity classes Graph algorithms

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pattern recognition Applications and Methods 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Maria De Marsico Gabriella Sanniti di Baja Ana Fred

ISBN: (数字)9783031245381

ISBN: (纸本)9783031245374

this book contains revised and extended versions of selected papers from the 10th and 11;international conference on pattern recognition, ICPRAM 2021 and 2022, held in February 2021 and 2022. Due to COVID-19 pandemic the conferences were held virtually. Both conferences received in total 204 submissions from which 8 full papers were carefully reviewed and selected for presentation in this volume. the papers span a wide range of investigation as well as development lines, which of course always reflect the last trends of research in the pattern recognition community.

关键词： pattern recognition Machine Learning Computer Systems Organization and Communication Networks Computer Applications Information Systems and Communication Service

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Combined Center-Symmetric Local patterns for Image recognition 4th

Combined Center-Symmetric Local Patterns for Image Recogniti...

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4th international conference on Information Systems Design and Intelligent Applications (INDIA)

作者： Parsi, Bhargav Tyagi, Kunal Malwe, Shweta R. Indian Sch Mines Indian Inst Technol Dhanbad 826004 Bihar India

ISBN: (纸本)9789811075124;9789811075117

Local feature description is gaining a lot of attention in the fields of texture classification, image recognition, and face recognition. In this paper, we propose Center-Symmetric Local Derivative Mapped patterns (CS-LDMP) and eXtended Center-Symmetric Local Mapped patterns (XCS-LMP) for local description of images. Strengths from Center-Symmetric Local Derivative pattern (CS-LDP) which is gaining more texture information and Center-Symmetric Local Mapped pattern (CS-LMP) which is capturing nuances between images were combined to make the CS-LDMP, and similarly, we combined CS-LMP and eXtended Center-Symmetric Local Binary pattern (XCS-LBP), which is tolerant to illumination changes and noise were combined to form XCS-LMP. the experiments were conducted on the CIFAR10 dataset and hence proved that CS-LDMP and XCS-LMP perform better than its direct competitors.

关键词： Local binary pattern Local mapped pattern Local derivative pattern Background subtraction Image recognition

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Backtracking algorithm for fast computing misdetection probability of sync word in burst synchronization

Backtracking algorithm for fast computing misdetection proba...

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10th international conference on Communication Technology (ICCT 2006)

作者： Yu, Hua Liang, Jian Ding, Quanlong Wei, Gang South China Univ Technol Sch Elect & Informat Engn Guangzhou 510640 Peoples R China

ISBN: (纸本)9781424408009

the frame sync word (SW) is very important for burst data communication systems. the misdetection (including false alarm and detection failure) probability is a very good performance metric of a SW. Usually, the exact misdetection probability of one SW is obtained by Exhaustively Full Searching (EFS) through the whole error pattern space. EFS is straightforward, but the drawback is complexity. In this paper, we propose a new full search algorithm-Backtracking Full Searching (BFS), which is based on the backtracking method. Simulation result shows that BFS algorithm is very efficient and flexible.

关键词： Fast response computer systems

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A Smart Home Agriculture System Based on Internet of things 10

A Smart Home Agriculture System Based on Internet of Things

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10th Mediterranean conference on Embedded computing, MECO 2021

作者： Akram, Vahid Khalilpour Challenger, Moharram International Computer Institute Ege University Bornova Izmir Turkey University of Antwerp and Flanders Make Flanders Belgium

ISBN: (纸本)9780738133614

Internet of things (IoT) has a growing application in agriculture and smart farming. Different monitoring, controlling and tracking systems have been proposed for increasing the efficiency and quality of agricultural products. While most of the existing systems focus on industrial farming, many people would like to create their own small-scale farms at home to produce organic products for their daily consumption. However, due to the lack of agricultural knowledge and infrastructures, people usually unable to produce healthy agricultural products at home. this paper proposes an IoT-based system for home agriculture to create small-scale farms in indoor locations. the proposed system uses ESP-32 devices and connected sensors to measure different quantities of the soil and air conditions to create a more suitable environment for growing the plants. Using the mobile application, the users can connect and configure the sensing devices over Bluetooth connections. the sensed data are sent to a web server over a WiFi connection. the web server stores the received data and provides real-time reports about the environment and plants. Based on the received data and the plant requirements, the webserver may send notification messages to the user's mobile phone. © 2021 IEEE.

关键词： Internet of things

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ICSOFT-PT 2015 - 10th international conference on Software Paradigm Trends, Proceedings;Part of 10th international Joint conference on Software Technologies, ICSOFT 2015

ICSOFT-PT 2015 - 10th International Conference on Software P...

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10th international conference on Software Paradigm Trends, ICSOFT-PT 2015

ISBN: (纸本)9789897581151

the proceedings contain 17 papers. the topics discussed include: SuperMod - a model-driven tool that combines version control and software product line engineering;semantic version management based on formal certification;Java-meets Eclipse - an IDE for teaching Java following the object-later approach;systematic identification of information flows from requirements to support privacy impact assessments;model checking to improve precision of design pattern instances identification in OO systems;transformation from R-UML to R-TNCES: new formal solution for verification of flexible control systems;a tool for management of knowledge dispersed throughout multiple references;a pi-calculus-based approach for the verification of UML2 sequence diagrams;on a-posteriori integration of Ecore models and hand-written Java code;OCL for rich domain models implementation - an incremental aspect based solution;and novel approach for computing skyline services with fuzzy consistent model for QoS- based service composition.

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Research on equipment health prediction technology based on edge computing and VAE-TCN 10

Research on equipment health prediction technology based on ...

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10th Annual international conference of Information and Communication Technology (ICICT)

作者： Yang, Yanfang Yu, Bo Wang, Wei Chinese Acad Sci Shenyang Inst Comp Technol Shenyang 110168 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Northeastern Univ Sch Comp Sci & Engn Shenyang 110169 Peoples R China

the Internet of things technology is developing rapidly, and the data generated has also exploded. Traditional cloud computing technology can no longer meet the demand for efficient processing of massive data. Edge computing technology can move the amount of calculation down to the edge of the network, which can greatly improve computing efficiency. Applying edge computing to the field of equipment health prediction, the combination of strong responsiveness and computing capabilities of edge computing and high-precision prediction technology makes production operation and maintenance more reliable and efficient. At the same time, a neural network prediction model combining Variational Auto-Encoder (VAE) and Time Convolutional Network (TCN) is proposed to improve the accuracy of equipment health prediction. this model uses VAE for dimensionality reduction, extracts the hidden information in the original data, reconstructs high-quality sample data, and then uses TCN to mine the internal connection between the features and the target in the long sequence information. Compared with five benchmark prediction models on the C-MAPSS dataset, experiments show that the proposed model has higher prediction accuracy. (C) 2021 the Authors. Published by Elsevier B.V.

关键词： edge computing equipment health prediction Variational Auto-Encoder Time Convolution Network

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Modified Jakubowski Shape Transducer for Detecting Osteophytes and Erosions in Finger Joints

Modified Jakubowski Shape Transducer for Detecting Osteophyt...

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10th international conference on Artificial Neural Networks and Genetic Algorithms

作者： Bielecka, Marzena Bielecki, Andrzej Korkosz, Mariusz Skomorowski, Marek Wojciechowski, Wadim Zielinski, Bartosz AGH Univ Sci & Technol Dept Geoinformat & Appl Comp Sci Fac Geol Geophys & Environm Protect Mickiewicza 30 PL-30059 Krakow Poland Jagiellonian Univ Inst Comp Sci PL-30348 Krakow Poland Jagiellonian Univ Hosp Dept Internal Med & Gerontol Div Rheumat PL-31531 Krakow Poland Jagiellonian Univ Hosp Dept Radiol PL-31531 Krakow Poland

ISBN: (纸本)9783642202667

In this paper, a syntactic method of pattern recognition is applied to hand radiographs interpretation, in order to recognize erosions and osteophytes in the finger joints. It is shown that, the classical Jakubowski transducer does not distinguish contours of healthy bones from contours of affected bones. therefore, the modifications of the transducer are introduced: It is demonstrated, that the modified transducer correctly recognizes the classes of bone shapes obtained based on the medical classification: healthy bone class, erosion bone class and osteophyte bone class.

关键词： Syntactic method of pattern recognition Medical imaging Computer assisted rheumatic diagnosis

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PPS: A Packets pattern-based Video Identification in Encrypted Network Traffic 16

PPS: A Packets Pattern-based Video Identification in Encrypt...

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16th IEEE/ACM international conference on Utility and Cloud computing (UCC) / 10th IEEE/ACM international conference on Big Data computing, Applications and Technologies (BDCAT)

作者： Bukhari, Syed M. A. H. Afaq, Muhammad Song, Wang-Cheol Jeju Natl Univ Dept Comp Engn Jeju City South Korea

ISBN: (纸本)9798400702341

Video identification in encrypted network traffic has become a trending field in the research area for user behavior and Quality of Experience (QoE) analysis. However, the traditional methods of video identification have become ineffective with the usage of Hypertext Transfer Protocol Secure (HTTPS). this paper presents a video identification method in encrypted network traffic using the number of packets received at the user's end in a second. For this purpose, video streams are captured, and feature is extracted from the video streams in the form of a series of Packets per Seconds (PPS). this feature is provided as input to a Convolutional Neural Network (CNN), which learns the pattern from the network traffic feature and successfully identifies the video even if the pattern differs from the training sample. the results show that PPS outperforms the other video identification techniques with a high accuracy of 90%. Moreover, the results show that CNN outperforms its counterpart regarding video identification with a 25% performance increase.

关键词： video identification packets per seconds encrypted network traffic video title classification

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