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检索条件"任意字段=5th International Conference on Pattern Recognition in Bioinformatics"

共 1406 条记录，以下是411-420 订阅

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Study on the spatial and temporal pattern of qinghai lake area in the past 50 years 5th

Study on the spatial and temporal pattern of qinghai lake ar...

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5th international conference on Geo-Spatial Knowledge and Intelligence, GSKI 2017

作者： Liu, Baokang Du, Yu’e He, Weiguo Duan, Shuiqiang Liang, Tiangang Qinghai Institute of Meteorological Sciences Xining810001 China Key Laboratory of Disaster Prevention and Mitigation in Qinghai Province Xining810001 China Natural Energy Research Institute Gansu Academy of Sciences Lanzhou730000 China College of Pastoral Agriculture Science and Technology Lanzhou University Lanzhou730000 China Information Science School Guangdong University of Finance and Economics Guangzhou510320 China Hydrology and Water Resource Bureau of Qinghai Province Xining810001 China

ISBN: (纸本)9789811308956

Lakes are not only the essential water resources for life, but also the sensitive indicators of climate change. the change of Lake area has a direct impact on the regulation of ecological environment. the area changes of shoreline were analyzed by using Multi-source Satellite Data and water identification model of Qinghai Lake in the past 50 years, the main conclusions are as follows: (1) the monitoring accuracy of Qinghai Lake area can significantly be improved by using multi-source high satellite data;(2) the experience threshold model based on the combination multi band with single band has a higher recognition accuracy of water when monitoring the area of the Qinghai Lake;(3) In recent 50 years, although the Qinghai Lake area of the stage showed an decreasing trend, since the beginning of twenty-first Century, the Qinghai Lake area increased, especially significantly in 2010, the Qinghai Lake area has been close to in 1995. But overall, still showed a decreasing trend;the analysis of area change in dry and wet season showed that the Qinghai Lake area were increased (R2 = 0.805 and 0.861, P © Springer Nature Singapore Pte Ltd. 2018.

关键词： Lakes

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State recognition of Egg Embryo in Vaccines Production Based on SVM 5

State Recognition of Egg Embryo in Vaccines Production Based...

引用

5th international conference on Mechanical, Automotive and Materials Engineering (CMAME)

作者： Xu, Yanwei Chen, Menghui Xie, Tancheng Henan Univ Sci & Technol Sch Mechatron Engn Luoyang 471023 Peoples R China

ISBN: (纸本)9781538604328

the method for state recognition of egg embryo in biological vaccines production based on computer image processing and support vector machine was researched. Firstly, the median filtering method was applied to eliminate noises in the images of egg embryo that were classified by the requirements of practical production, then the threshold segmentation method was used to segment the images, then the blood vessels and black blocks in the egg embryo images were selected as major characteristics to extract. the decision tree classification model with structure of binary tree was built on support vector machine, and the model was trained with the toolkit LIBSVM, the penalty factor C = 2, RBF kernel parameter gamma=3.0512e-05 and the precision of cross validation accuracy is 98.913% Finally, 100 egg embryos were randomly selected as the test samples to do pattern recognition, and compared with manual test result. the comparison result showed that the discriminant accuracy of SVM classifier on weak embryo, polluted embryo or dead embryo was 100%, and it of SVM classifier on live embryo was 94.62%.

关键词： egg embryo pattern recognition support vector machine computer image processing

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pattern recognition for Automated Healthcare Assessment Using Non-Invasive, Ambient Sensors 5

Pattern Recognition for Automated Healthcare Assessment Usin...

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5th IEEE international conference on Healthcare Informatics (ICHI)

作者： Nienhold, Dino Dornberger, Rolf Korkut, Safak Univ Appl Sci & Arts Northwestern Switzerland Inst Informat Syst Sch Business Basel Switzerland

ISBN: (纸本)9781509048816

In this paper, a solution for an automated healthcare assessment process is proposed. Non-invasive, ambient sensors are retrieving data from patients being in their home care treatment setups. the type of sensors is limited to the tracking of inertia, motion, and alcohol gas. Low-cost sensor prototypes are developed. they constantly measure the movement and the air around the patients. the Big Data generated in this way is used to retrieve patterns of activities. Different pattern recognition algorithms are tested and compared. the highest accuracy and reliability in assessing the data are support vector machines and feedforward neural networks with a performance of 90 % probability in identifying the correct patients' activities over the test period. In this paper, the setup of the sensor prototypes, the data handling, and the data analytics are discussed.

关键词： Data Analytics pattern recognition Internet of things Wearable Sensors Inertial Sensors Automated Healthcare Assessment

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Gaze Based Behavior Analysis of Online Learners 17

Gaze Based Behavior Analysis of Online Learners

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5th international conference on Information and Education Technology (ICIET)

作者： Liu, Wei Fan, Zijian Liu, Feifan Xu, Jing Cheng, Wenqing Huazhong Univ Sci & Technol Sch EIC Wuhan Hubei Peoples R China Huazhong Univ Sci & Technol Wuhan Hubei Peoples R China

ISBN: (纸本)9781450348034

With the development of Internet technology and increasingly rich online curriculum resources, e-learning is becoming more and more popular. Although the e-learning systems can record some interactions of online learners, these records cannot reflect the physical behaviors of the learners during the learning process, such as the thinking duration and the watching focus. the measurement and recognition of these physical behaviors is helpful for the evaluation of learning process. In this paper, a kind of measurement tool, based on the Tobii eye tracker, is developed to collect the learner's gaze movement data and recognize the corresponding learning behavior pattern. Two metrics, namely saccade distance and horizon movement proportion, are proposed to describe the gaze movement of online learners. Total three kinds of learning behavior patterns, including reading courseware, typing text and watching video clips, are considered in our tool. A polynomial fitting model is developed to recognize them from the measured gaze movement data. the experiments show that this tool can distinguish the three kinds of learning behavior patterns with acceptable errors, and it can be used for analyzing the behavior of online learners.

关键词： Learning behavior Gaze movement Behavior pattern

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5th international conference on Mining Intelligence and Knowledge Exploration, MIKE 2017

5th International Conference on Mining Intelligence and Know...

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5th international conference on Mining Intelligence and Knowledge Exploration, MIKE 2017

ISBN: (纸本)9783319719276

the proceedings contain 40 papers. the special focus in this conference is on Mining Intelligence and Knowledge Exploration. the topics include: Despeckling with structure preservation in clinical ultrasound images using historical edge information weighted regularizer;fingerprint image quality assessment and scoring;pattern based information retrieval approach to discover extremist information on the internet;improved community interaction through context based citation analysis;Portfolio optimization in dynamic environments using MemSPEAII;a multi-objective evolutionary algorithm for color image segmentation;Face recognition by RBF with wavelet, DCV and modified LBP operator face representation methods;DNN-HMM acoustic modeling for large vocabulary Telugu speech recognition;emotion recognition through facial gestures - a deep learning approach;memetic algorithm based on global-best harmony search and hill climbing for part of speech tagging;a study on crossmodal correspondence in sensory pathways through forced choice task and frequency based correlation in sound-symbolism;point process modeling of spectral peaks for low resource robust speech recognition;Significance of DNN-AM for multimodal sentiment analysis;a concept driven graph based approach for estimating the focus time of a document;query morphing: A proximity-based approach for data exploration and query reformulation;wikiSeeAlso: Suggesting tangentially related concepts (see also links) for wikipedia articles;integrating knowledge encoded by linguistic phenomena of Indian languages with neural machine translation;partitioned-based clustering approaches for single document extractive text summarization;Supervised approaches to assign cooperative patent classification (CPC) codes to patents;arousal prediction of news articles in social media;mining informative words from the tweets for detecting the resources during disaster.

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Proceedings - 2017 5th international conference on Applied Computing and Information Technology, 2017 4th international conference on Computational Science/Intelligence and Applied Informatics and 2017 1st international conference on Big Data, Cloud Computing, Data Science and Engineering, ACIT-CSII-BCD 2017

Proceedings - 2017 5th International Conference on Applied C...

引用

5th international conference on Applied Computing and Information Technology, 2017 4th international conference on Computational Science/Intelligence and Applied Informatics and 2017 1st international conference on Big Data, Cloud Computing, Data Science and Engineering, ACIT-CSII-BCD 2017

ISBN: (纸本)9781538633021

the proceedings contain 44 papers. the topics discussed include: a learning material for physics experiment with high-accuracy using computer vision technique;automatic classification of remarks in werewolf BBS;a rapid incremental frequent pattern mining algorithm for uncertain data;global and local bursts detection in streaming data;two-mode three-way dominance points model for periodic dissimilarity;an intelligent noninvasive taste detection app for watermelons;automated risk identification of CMMI project planning using ontology;and depth recognition in 3D translucent stereoscopic imaging of medical volumes by means of a glasses-free 3d display.

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Fusion with CS-LBP and HOG for Vehicle Make and Model recognition

Fusion with CS-LBP and HOG for Vehicle Make and Model Recogn...

引用

2017 5th international conference on Mechatronics,Materials,Chemistry and Computer Engineering(ICMMCCE 2017)

作者： Zhu Shanwei Li Yuhui Feng Jin Zhang Lingfeng College of Information Engineering and Automation Kunming University of Science and Technology

ISBN: (纸本)9789462523814

Local binary pattern(LBP) has widely used in face recognition with extracting texture feature, for the high statistical histogram dimensions of LBP and unable to effectively express the edge and direction information of image, so a method which is called fusion with blocking CS-LBP and HOG features is proposed, and applied vehicle recognition. At first, the vehicle image is extracted texture feature with blocking CS-LBP operator, which is calculated the texture histogram for each sub-block, and then the HOG feature of the original image is extracted, as well as the HOG feature which is based on the CS-LBP, finally, the blocking CS-LBP feature is fused with these two different HOG features. the experiments are implemented on the vehicle image databases, the results show that the proposed method can be obtained a higher recognition with K neighbor classification.

关键词： vehicle recognition local binary pattern HOG feature blocking CS-LBP

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Biometric recognition based on Palm Vein Image Using Learning Vector Quantization 5

Biometric Recognition based on Palm Vein Image Using Learnin...

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5th international conference on Instrumentation, Communications, Information Technology, and Biomedical Engineering (ICICI-BME)

作者： Setiawan, Herry Yuniarno, Eko Mulyanto Polytech South Acch Dept Comp Sci Tapaktuan Indonesia Inst Technol Sepuluh Nopember Dept Elect Engn Surabaya Indonesia

ISBN: (纸本)9781538634554

Every human being has its own uniqueness among humans that other good physical form or characteristic trait. Biometrics is the science that can recognize a part of an individual. therefore, biometric identification is one of the ways that is done to identify the identity of the person. Palm vein biometric is one who lately attracted many researchers and industry because it has several advantages over other physical characteristics such as fingerprint, iris and face. Palm vein has internal features making it difficult undermined, modified and simulated with fake palms. In this study, design and implementation will do a recognition system through the venous vessels. Systems that were built capable of taking images of the Palm veins, detect the presence of venous vessels are then able to tell based on the database. this is done after the process of extraction, processing and manufacturing characteristics against the image of Palm vein vessels. the method used is the phase and learning vector quantization symmetri. Feature extraction using phase symmetri. phase symmetri applied by calculating the amplitude and phase of the signal frequency of the image of the vein which represents detailed information detailed variant of an image of the vein. While learning vector quantization is used for grouping the exclusive result of extraction. this research resulted in the classification with accuracy reaching 94%

关键词： Biometric pattern recognition palm vein learning vector quantization phase symmetri

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Face recognition by RBF with wavelet, DCV and modified LBP operator face representation methods 1

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5th international conference on Mining Intelligence and Knowledge Exploration, MIKE 2017

作者： Jebakumari Beulah Vasanthi, J. Kathirvalavakumar, T. Department of Computer Science ANJA College SivakasiTamilnadu India Department of Computer Science VHNSN College VirudhunagarTamilnadu India

ISBN: (数字)9783319719283

ISBN: (纸本)9783319719276

A face recognition system must be robust with respect to many variability such as viewpoint, illumination, and facial expression of the face image. the main aim of the proposed work is to represent and recognize face images with different poses. An efficient face recognition system with face image representation using wavelet and averaged wavelet packet coefficients in the form of Discriminative Common Vector (DCV) and modified Local Binary patterns (LBP) and recognition using radial basis function (RBF) neural network is presented. Face images are decomposed by 2-level two-dimensional (2-D) wavelet and wavelet packet transformation. the discriminative common vectors are obtained for wavelet and averaged wavelet packet coefficients. Newly proposed LBP operator is applied on the DCV and LBPs are obtained. Histogram values are generated for the LBP and recognized using RBF network. the proposed work is tested on three standard face databases namely Olivetti-Oracle Research Lab (ORL), Japanese Female Facial Expression (JAFFE) and Essex face database. the extracted features are recognized by the proposed method results in good recognition rates. the execution time for the proposed methods is also less because of the meaningful extracted features obtained from the face representation methods. © 2017, Springer international Publishing AG.

关键词： Local binary pattern

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5th international Workshop on New Frontiers in Mining Complex patterns, NFMCP 2016 was held in conjunction with the European conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML-PKDD 2016

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5th international Workshop on New Frontiers in Mining Complex patterns, NFMCP 2016 was held in conjunction with the European conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML-PKDD 2016

ISBN: (纸本)9783319614601

the proceedings contain 16 papers. the special focus in this conference is on New Frontiers in Mining Complex patterns. the topics include: Feature induction and network mining with clustering tree ensembles;feature ranking and selection via eigenvector centrality;Bayesian confirmation measures in rule-based classification;audio-based speed change classification for vehicles;a statistical approach to speaker identification in forensic phonetics;increasing the interpretability of rules induced from imbalanced data by using Bayesian confirmation measures;analyzing time-decay effects of mediating objects in creating trust-links;feature clustering for extreme events analysis, with application to extreme stream-flow data;profiling human behavior through multidimensional latent factor modeling;subgraph mining for anomalous pattern discovery in event logs;mining spatio-temporal patterns of periodic changes in climate data;mining keystroke timing pattern for user authentication and mining chess playing as a complex process.

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