GraphiCon'2019 Proceedings. Volume 2最新文献_第2页

Determination of Plant Phenological Cycle From RGB Images 利用RGB图像测定植物物候周期

GraphiCon'2019 Proceedings. Volume 2 Pub Date : 2019-11-11 DOI: 10.30987/graphicon-2019-2-178-181

Михаил Германович Катаев, M. Kataev, Кирилл Ёлгин, Kirill Yolgin

引用次数: 0

Image Colorization 图像彩色化

GraphiCon'2019 Proceedings. Volume 2 Pub Date : 2019-11-11 DOI: 10.30987/graphicon-2019-2-207-210

Дарья Михалина, Daria Mikhalina, Александр Кузьменко, A. Kuz'menko, Константин Дергачев, K. Dergachev, Виталий Шкаберин, Vitaliy Shkaberin

{"title":"Image Colorization","authors":"Дарья Михалина, Daria Mikhalina, Александр Кузьменко, A. Kuz'menko, Константин Дергачев, K. Dergachev, Виталий Шкаберин, Vitaliy Shkaberin","doi":"10.30987/graphicon-2019-2-207-210","DOIUrl":"https://doi.org/10.30987/graphicon-2019-2-207-210","url":null,"abstract":"The article discusses one of the latest ways to colorize a black and white image using deep learning methods. For colorization, a convolutional neural network with a large number of layers (Deep convolutional) is used, the architecture of which includes a ResNet model. This model was pre-trained on images of the ImageNet dataset. A neural network receives a black and white image and returns a colorized color. Since, due to the characteristics of ResNet, an input multiple of 255 is received, a program was written that, using frames, enlarges the image for the required size. During the operation of the neural network, the CIE Lab color model is used, which allows to separate the black and white component of the image from the color. For training the neural network, the Place 365 dataset was used, containing 365 different classes, such as animals, landscape elements, people, and so on. The training was carried out on the Nvidia GTX 1080 video card. The result was a trained neural network capable of colorizing images of any size and format. As example we had a speed of 0.08 seconds and an image of 256 by 256 pixels in size. In connection with the concept of the dataset used for training, the resulting model is focused on the recognition of natural landscapes and urban areas.","PeriodicalId":409819,"journal":{"name":"GraphiCon'2019 Proceedings. Volume 2","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133352670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Identification of Semantic Patterns in Full-text Documents Using Neural Network Methods 基于神经网络方法的全文文档语义模式识别

GraphiCon'2019 Proceedings. Volume 2 Pub Date : 2019-11-11 DOI: 10.30987/graphicon-2019-2-276-279

Олег Золотарев, O. Zolotarev, Ярослав Соломенцев, Yaroslav K. Solomentsev, Аида Хакимова, Aida Khakimova, Михаил Шарнин, M. Charnine

引用次数: 6

Ergonomic Adjustments of a Website Due to Changes in Preferences and Mechanisms of Information Perception by People 基于偏好变化和信息感知机制的网站人机工程学调整

GraphiCon'2019 Proceedings. Volume 2 Pub Date : 2019-11-11 DOI: 10.30987/graphicon-2019-2-211-214

Владимир Иосифович Евенко, V. Evenko, Алина Пузачева, Alina Puzacheva, Диана Беликова, Diana Belikova

引用次数: 1

Modern Methods of Usability Engineering of User Interface for Weboriented Environment 面向web环境的用户界面可用性工程的现代方法

GraphiCon'2019 Proceedings. Volume 2 Pub Date : 2019-11-11 DOI: 10.30987/graphicon-2019-2-215-218

Александр Кузьменко, A. Kuz'menko, Андрей Аверченков, A. Averchenkov, Виталий Шкаберин, Vitaliy Shkaberin

引用次数: 1

Applying Visual Analysis Procedures to Multidimensional Medical Data 多维医学数据可视化分析程序的应用

GraphiCon'2019 Proceedings. Volume 2 Pub Date : 2019-11-11 DOI: 10.30987/graphicon-2019-2-122-126

Александр Бондарев, A. Bondarev, Владимир Галактионов, V. Galaktionov

引用次数: 2

Simulation of Contractile Heart Function in the Autodesk Maya Environment Based on Muscle Fiber Macro-Structure 在Autodesk Maya环境中基于肌肉纤维宏观结构的心脏收缩功能模拟

GraphiCon'2019 Proceedings. Volume 2 Pub Date : 2019-11-11 DOI: 10.30987/graphicon-2019-2-227-331

Мария Титова, M. Titova, Татьяна Томчинская, T. Tomchinskaya

{"title":"Simulation of Contractile Heart Function in the Autodesk Maya Environment Based on Muscle Fiber Macro-Structure","authors":"Мария Титова, M. Titova, Татьяна Томчинская, T. Tomchinskaya","doi":"10.30987/graphicon-2019-2-227-331","DOIUrl":"https://doi.org/10.30987/graphicon-2019-2-227-331","url":null,"abstract":"A dynamic simulation model of the contractile function of the heart is presented. The contractile function simulation is based on the modeling of the muscle fibers' structure according to the Atlas of human anatomy and the use of parameters of their geometric shape as parameters that control the contraction. The basic concepts of the architecture of muscle fibers of the myocardium and the structure of the blood supply to the heart are investigated. An algorithm is developed for local parameterization of the contractile function of the heart, which mimics blood flow and conduction disturbances via special control functions. The algorithm of the simulation model is shown in the example of only the left ventricle of the heart but is embedded in the full three-dimensional model of the ventricular complex of the heart. The simulation model is implemented as a solid-state parameterized model in the Autodesk Maya tool environment, managed by a program in the embedded Python language. The result is compared with the results of the OpenCMISS software in favor of the latter. It is planned to continue work with the implementation of the most advanced concept of the myocardial architecture of Torrent-Guasp together with the networks of electrical excitation and blood supply.","PeriodicalId":409819,"journal":{"name":"GraphiCon'2019 Proceedings. Volume 2","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132561166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Construction of a Generalized Computational Experiment and Visual Analysis of Multidimensional Data 广义计算实验的构建与多维数据的可视化分析

GraphiCon'2019 Proceedings. Volume 2 Pub Date : 2019-11-11 DOI: 10.30987/graphicon-2019-2-117-121

Александр Бондарев, A. Bondarev, Владимир Галактионов, V. Galaktionov

{"title":"Construction of a Generalized Computational Experiment and Visual Analysis of Multidimensional Data","authors":"Александр Бондарев, A. Bondarev, Владимир Галактионов, V. Galaktionov","doi":"10.30987/graphicon-2019-2-117-121","DOIUrl":"https://doi.org/10.30987/graphicon-2019-2-117-121","url":null,"abstract":"The work is devoted to the problems of constructing a generalized computational experiment in the problems of computational aerodynamics. The construction of a generalized computational experiment is based on the possibility of carrying out parallel calculations of the same problem with different input data in multitasking mode. This allows carrying out parametric studies and solving problems of optimization analysis. The results of such an experiment are multidimensional arrays, for the study of which visual analytics methods should be used. The construction of a generalized experiment allows one to obtain dependences for valuable functionals on the determining parameters of the problem under consideration. The implementation of a generalized experiment allows one to obtain a solution for a class of problems in the ranges under consideration, and not just for one problem. Examples of constructing a generalized computational experiment for various classes of problems of computational aerodynamics are presented. The article also provides an example of constructing such an experiment for a comparative assessment of the accuracy of numerical methods.","PeriodicalId":409819,"journal":{"name":"GraphiCon'2019 Proceedings. Volume 2","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128124717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

The Combination of Morphological and Evolutionary Algorithms for Graph-based Pathfinding on Maps with Complex Topologies 复杂拓扑地图上基于图的寻路的形态学和进化算法的结合

GraphiCon'2019 Proceedings. Volume 2 Pub Date : 2019-11-11 DOI: 10.30987/graphicon-2019-2-300-303

Игорь Савостин, Igor' Savostin, Андрей Трубаков, A. Trubakov

引用次数: 1

Complexity of EEG Signals in Schizophrenia Syndromes 精神分裂症综合征脑电图信号的复杂性

GraphiCon'2019 Proceedings. Volume 2 Pub Date : 2019-11-11 DOI: 10.30987/graphicon-2019-2-140-143

I. E. Kutepov, V. Krysko, A. Krysko, S. Pavlov, M. V. Zigalov, I. Papkova, O. Saltykova, T. Y. Yaroshenko, E. Krylova, T. V. Yakovleva, V. Dobriyan, N. Erofeev

{"title":"Complexity of EEG Signals in Schizophrenia Syndromes","authors":"I. E. Kutepov, V. Krysko, A. Krysko, S. Pavlov, M. V. Zigalov, I. Papkova, O. Saltykova, T. Y. Yaroshenko, E. Krylova, T. V. Yakovleva, V. Dobriyan, N. Erofeev","doi":"10.30987/graphicon-2019-2-140-143","DOIUrl":"https://doi.org/10.30987/graphicon-2019-2-140-143","url":null,"abstract":"In the present study, 45 patients with schizophrenia syndromes and 39 healthy subjects are studied with electroencephalogram (EEG) signals. The study groups were of different genders. For each of the two groups, the signals were analyzed using 16 EEG channels. Multiscale entropy, Lempel-Ziv complexity and Lyapunov exponent were used to study the chaotic signals. The data were compared for two groups of subjects. Entropy was compared for each of the 16 channels for all subjects. As a result, topographic images of brain areas were obtained, illustrating the entropy and complexity of Lempel-Ziv. Lempel-Ziv complexity was found to be more representative of the classification problem. The results will be useful for further development of EEG signal classification algorithms for machine learning. This study shows that EEG signals can be an effective tool for classifying participants with symptoms of schizophrenia and control group. It is suggested that this analysis may be an additional tool to help psychiatrists diagnose patients with schizophrenia.","PeriodicalId":409819,"journal":{"name":"GraphiCon'2019 Proceedings. Volume 2","volume":"41 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131923284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6