Dichotomizing compression of the graphic images

2002 ◽  
Author(s):  
D. Sukhanov ◽  
A. Sukhanov
Keyword(s):  
Graphic Images

Deep Learning Based Classification of Time Series of Chaotic Systems over Graphic Images

2021 ◽  
Author(s):  
Süleyman UZUN ◽  
Sezgin KAÇAR ◽  
Burak ARICIOĞLU
Keyword(s):  
Time Series ◽  
Deep Learning ◽  
Transfer Learning ◽  
Chaotic Systems ◽  
Initial Conditions ◽  
Step Size ◽  
Learning Methods ◽  
Data Set ◽  
Graphic Images ◽  
Different Chaotic Systems

Abstract In this study, for the first time in the literature, identification of different chaotic systems by classifying graphic images of their time series with deep learning methods is aimed. For this purpose, a data set is generated that consists of the graphic images of time series of the most known three chaotic systems: Lorenz, Chen, and Rossler systems. The time series are obtained for different parameter values, initial conditions, step size and time lengths. After generating the data set, a high-accuracy classification is performed by using transfer learning method. In the study, the most accepted deep learning models of the transfer learning methods are employed. These models are SqueezeNet, VGG-19, AlexNet, ResNet50, ResNet101, DenseNet201, ShuffleNet and GoogLeNet. As a result of the study, classification accuracy is found between 96% and 97% depending on the problem. Thus, this study makes association of real time random signals with a mathematical system possible.

scholarly journals ABOUT THE STRESS STATE ON THE CONTOURS OF UNDERGROUND HORIZONTAL WORKINGS, SUBJECT TO AN OVERALL UNIFORM PRESSURE

2019 ◽  
Vol 7 (1) ◽  
pp. 49-60
Author(s):  
Оксана Богомолова ◽  
Oksana Bogomolova ◽  
Андрей Ушаков ◽  
Andrej Ushakov
Keyword(s):  
Stress State ◽  
Cross Section ◽  
Expansion Coefficient ◽  
Uniform Pressure ◽  
Lateral Expansion ◽  
Underground Workings ◽  
The Cross ◽  
Graphic Images ◽  
The Given ◽  
Distribution Of Stresses

The paper presents the results of a study on the distribution of stresses on the contours of underground workings, the cross section of which has the form of a trapezoid and an ellipse. The distribution of stresses at the points of workings contours is obtained at the given values of uniform pressure and the lateral expansion coefficient of the rock. The graphic images of stress diagrams acting on the contours of the considered workings are given.

DEVELOPEMENT AN ALGORITM FOR RECOGNIZING TEXT DATA IN DIGITAL GRAPHIC IMAGES

2021 ◽  
pp. 75-78
Author(s):  
Н.Н. Беляев ◽  
О.А. Бебенина ◽  
В.Е. Бородкина
Keyword(s):  
Frequency Domain ◽  
Recognition Algorithm ◽  
Statistical Characteristics ◽  
Discrete Cosine Transformation ◽  
Text Data ◽  
Jpeg Images ◽  
Statistical Classifiers ◽  
Distribution Of Values ◽  
Data Content ◽  
Graphic Images

Предложен алгоритм распознавания, реализующий процедуры: обучения выбранных классификаторов и распознавания текстовых данных, учитывающие статистические характеристики распределения коэффициентов частотной области цифровых графических изображениях формата JPEG. The article presents an approach to development an algorithm for recognizing text data within JPEG format digital graphic images. Considered a hypothesis about influence text data content in JPEG digital graphic images on the distribution of values of the discrete cosine transformation coefficients in the frequency domain JPEG images of the format. Statistical classifiers models that provide a solution to the problem of recognition of text data in JPEG images based on analysis of its frequency domain have been determined. A recognition algorithm is proposed that implements the following procedures: training of selected classifiers and recognition of text data, taking into account the statistical characteristics of the distribution of frequency domain coefficients in JPEG format images.

Algorithm for Petro-Graphic Color Image Segmentation Used in Oil Exploration

2014 ◽  
pp. 187-195 ◽  
Keyword(s):  
Image Segmentation ◽  
Thin Section ◽  
Heuristic Algorithm ◽  
Color Image ◽  
Color Image Segmentation ◽  
Oil Exploration ◽  
Segmentation Method ◽  
Graphic Images ◽  
Oil Gas ◽  
Automatic Algorithm

A new heuristic algorithm for porosity segmentation for the colored petro-graphic images is proposed. The proposed algorithm automatically detects the porosities that represent the presence of oil, gas, or even water in the analyzed thin section rock segment based on the colour of the porosity area filled with dies in the analyzed sample. For the purpose of the oil exploration, the thin section fragments are died in order to emphasize the porosities that are analyzed under the microscope. The percentage of the porosity is directly proportional to the probability of the oil, gas, or even water presence in the area where the drilling is performed (i.e. the increased porosity indicates the higher probability of oil existence in the region). The proposed automatic algorithm shows better results than the existing K-means segmentation method.

Promoting calls to a quitline: quantifying the influence of message theme, strong negative emotions and graphic images in television advertisements

2011 ◽  
Vol 20 (4) ◽  
pp. 279-284 ◽  
Author(s):  
M. C. Farrelly ◽  
K. C. Davis ◽  
J. M. Nonnemaker ◽  
K. Kamyab ◽  
C. Jackson
Keyword(s):  
Negative Emotions ◽  
Television Advertisements ◽  
Graphic Images

The Emblems of the 1949 Geneva Conventions: their Content and Meaning

2000 ◽  
Vol 3 ◽  
pp. 258-272 ◽  
Author(s):  
Zidane Meriboute
Keyword(s):  
Human Beings ◽  
Common Heritage ◽  
Geneva Conventions ◽  
Vital Functions ◽  
The Common ◽  
Graphic Images

From time immemorial, human beings have communicated using signs of one kind or another, among them gestures and graphic images. Knowledge of these different forms of communication gradually spread, and they became part of the common heritage of peoples and of humanity as a whole. The respect inspired by signs and symbols stems from the fact that they perform vital functions, such as channeling knowledge, helping survival and protecting individuals and their communities.

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