scholarly journals Computer Multimedia Art Pattern Creation Based on P-Filling Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Wenli Lian
Keyword(s):  
Activation Function ◽  
Quality Education ◽  
Production Model ◽  
Parameter Control ◽  
Art Appreciation ◽  
Sigmoid Function ◽  
Art Teaching ◽  
Multimedia Art ◽  
Pattern Production ◽  
Education In China

Art education is an important part of quality education in China. It undertakes the important responsibility of cultivating students' aesthetic ability, art appreciation ability, art perception ability, and expression ability. In junior middle school art teaching, the skill of pattern creation is an ability that needs to be focused on cultivating students. The computer multimedia art patterns are currently created mainly relying on manual drawing. A computer multimedia art pattern production model is proposed based on the P-filling algorithm in this paper. After using the P-filling algorithm to quickly generate a large number of fake images and retrieve the code of the most recent damaged image, the code estimates the missing content by generating a model. On this basis, the semantic P-filling algorithm and the perceptual P-filling algorithm are combined, and the unsaturated region is enlarged by improving the activation function sigmoid function, which solves the problem that the gradient is easy to disappear. Experimental results show that, through this production model, users can produce a large number of computer multimedia art patterns with hand-drawn style features through very little interaction and parameter control.

Bio-inspired neural network with application to license plate recognition: hysteretic ELM approach

2016 ◽  
Vol 36 (2) ◽  
pp. 172-178 ◽  
Author(s):  
Liang Chen ◽  
Leitao Cui ◽  
Rong Huang ◽  
Zhengyun Ren
Keyword(s):  
Neural Network ◽  
Activation Function ◽  
Neural System ◽  
Learning System ◽  
License Plate ◽  
Sigmoid Function ◽  
License Plate Recognition ◽  
Content Type ◽  
Hidden Layer ◽  
Automatic License Plate Recognition

Purpose This paper aims to present a bio-inspired neural network for improvement of information processing capability of the existing artificial neural networks. Design/methodology/approach In the network, the authors introduce a property often found in biological neural system – hysteresis – as the neuron activation function and a bionic algorithm – extreme learning machine (ELM) – as the learning scheme. The authors give the gradient descent procedure to optimize parameters of the hysteretic function and develop an algorithm to online select ELM parameters, including number of the hidden-layer nodes and hidden-layer parameters. The algorithm combines the idea of the cross validation and random assignment in original ELM. Finally, the authors demonstrate the advantages of the hysteretic ELM neural network by applying it to automatic license plate recognition. Findings Experiments on automatic license plate recognition show that the bio-inspired learning system has better classification accuracy and generalization capability with consideration to efficiency. Originality/value Comparing with the conventional sigmoid function, hysteresis as the activation function enables has two advantages: the neuron’s output not only depends on its input but also on derivative information, which provides the neuron with memory; the hysteretic function can switch between the two segments, thus avoiding the neuron falling into local minima and having a quicker learning rate. The improved ELM algorithm in some extent makes up for declining performance because of original ELM’s complete randomness with the cost of a litter slower than before.

scholarly journals THE STUDY OF ACTIVATION FUNCTIONS IN DEEP LEARNING FOR PEDESTRIAN DETECTION AND TRACKING

2019 ◽  
Vol XLII-2/W12 ◽  
pp. 53-59 ◽  
Author(s):  
M. N. Favorskaya ◽  
V. V. Andreev
Keyword(s):  
Deep Learning ◽  
Pedestrian Detection ◽  
Linear Part ◽  
Activation Function ◽  
Sigmoid Function ◽  
Human Machine Interaction ◽  
Learning Stage ◽  
Detection And Tracking ◽  
Starting Point ◽  
Indoor Scenes

<p><strong>Abstract.</strong> Pedestrian detection and tracking remains a highlight research topic due to its paramount importance in the fields of video surveillance, human-machine interaction, and tracking analysis. At present time, pedestrian detection is still an open problem because of many challenges of image representation in the outdoor and indoor scenes. In recent years, deep learning, in particular Convolutional Neural Networks (CNNs) became the state-of-the-art in terms of accuracy in many computer vision tasks. The unsupervised learning of CNNs is still an open issue. In this paper, we study a matter of feature extraction using a special activation function. Most of CNNs share the same architecture, when each convolutional layer is followed by a nonlinear activation layer. The activation function Rectified Linear Unit (ReLU) is the most widely used as a fast alternative to sigmoid function. We propose a bounded randomized leaky ReLU working in such manner that the angle of linear part with the highest input values is tuned during learning stage, and this linear part can be directed not only upward but also downward using a variable bias for its starting point. The bounded randomized leaky ReLU was tested on Caltech Pedestrian Dataset with promising results.</p>

scholarly journals RESEARCH ON THE CURRENT SITUATION AND COUNTERMEASURES OF RURAL PHYSICAL EDUCATION IN CHINA

2021 ◽  
Author(s):  
MING-HANG LAI
Keyword(s):  
Physical Education ◽  
Current Situation ◽  
Quality Education ◽  
Economic Conditions ◽  
Education In China ◽  
Development Of Students

Physical education as a compulsory course to promote the all-round development of students, at the same time, with the continuous promotion of quality education, physical education has been significantly improved. However, compared with cities with better economic conditions, the current situation of rural physical education is not satisfactory. By using the methods of literature investigation and analysis, this paper discusses the current situation of rural physical education in China and puts forward some measures to promote the development of rural physical education in China.

scholarly journals Stability Analysis Based on Caputo-Type Fractional-Order Quantum Neural Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yumin Dong ◽  
Xiang Li ◽  
Wei Liao ◽  
Dong Hou
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Learning Algorithm ◽  
Activation Function ◽  
Linear Matrix ◽  
Mixed Delays ◽  
Sigmoid Function ◽  
Matrix Inequality ◽  
Fractional Quantum ◽  
Quantum Neural Network

In this paper, a quantum neural network with multilayer activation function is proposed by using multilayer Sigmoid function superposition and learning algorithm to adjust quantum interval. On this basis, the quasiuniform stability of fractional quantum neural networks with mixed delays is studied. According to the order of two different cases, the conditions of quasi uniform stability of networks are given by using the techniques of linear matrix inequality analysis, and the sufficiency of the conditions is proved. Finally, the feasibility of the conclusion is verified by experiments.

scholarly journals Based on the Current Situation and Thinking of Art Appreciation Education in Colleges and Universities

2020 ◽  
Vol 4 (10) ◽  
Author(s):  
Xin Li
Keyword(s):  
College Students ◽  
Coping Strategies ◽  
Quality Education ◽  
Art Appreciation ◽  
Art Educators ◽  
Depth Analysis ◽  
Art Works ◽  
The World ◽  
Elective Course

The development and progress of society put forward higher requirements for the comprehensive quality of contemporary college students. As a public elective course to strengthen quality education and improve students' art accomplishment, art appreciation course has its own discipline characteristics and teaching rules. It enriches students' aesthetic concept and always cultivates their art appreciation ability through aesthetic education of excellent art works and in all over the world. How to face all the students to popularize art knowledge and cultivate their aesthetic ability is a problem that art educators think about. This paper makes an in-depth analysis of their own conditions of non art majors and expounds the coping strategies. It is hoped that it will help to broaden students' art vision, improve their art accomplishment, enhance their humanistic quality and promote their all-round development.

Use of Binary Sigmoid Function And Linear Identity In Artificial Neural Networks For Forecasting Population Density

2017 ◽  
Vol 1 (1) ◽  
pp. 43 ◽  
Author(s):  
Anjar Wanto ◽  
Agus Perdana Windarto ◽  
Dedy Hartama ◽  
Iin Parlina
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Artificial Neural Network ◽  
Population Density ◽  
Network Architecture ◽  
Activation Function ◽  
Sigmoid Function ◽  
Backpropagation Algorithm ◽  
Architecture Model ◽  
Artificial Neural

Artificial Neural Network (ANN) is often used to solve forecasting cases. As in this study. The artificial neural network used is with backpropagation algorithm. The study focused on cases concerning overcrowding forecasting based District in Simalungun in Indonesia in 2010-2015. The data source comes from the Central Bureau of Statistics of Simalungun Regency. The population density forecasting its future will be processed using backpropagation algorithm focused on binary sigmoid function (logsig) and a linear function of identity (purelin) with 5 network architecture model used the 3-5-1, 3-10-1, 3-5 -10-1, 3-5-15-1 and 3-10-15-1. Results from 5 to architectural models using Neural Networks Backpropagation with binary sigmoid function and identity functions vary greatly, but the best is 3-5-1 models with an accuracy of 94%, MSE, and the epoch 0.0025448 6843 iterations. Thus, the use of binary sigmoid activation function (logsig) and the identity function (purelin) on Backpropagation Neural Networks for forecasting the population density is very good, as evidenced by the high accuracy results achieved.

scholarly journals Improved Time Training with Accuracy of Batch Back Propagation Algorithm Via Dynamic Learning Rate and Dynamic Momentum Factor

2018 ◽  
Vol 7 (4) ◽  
pp. 170
Author(s):  
Mohammed Sarhan Al_Duais ◽  
Fatma Susilawati. Mohamad
Keyword(s):  
Back Propagation ◽  
Activation Function ◽  
Learning Rate ◽  
Superior Performance ◽  
Sigmoid Function ◽  
Back Propagation Algorithm ◽  
Dynamic Learning ◽  
Propagation Algorithm ◽  
Dynamic Function ◽  
Xor Problem

<span lang="EN-US">The man problem of batch back propagation (BBP) algorithm is slow training and there are several parameters needs to be adjusted manually, also suffers from saturation training.</span><span lang="EN-US">The learning rate and momentum factor are significant parameters for increasing the efficiency of the (BBP). In this study, we created a new dynamic function of each learning rate and momentum facor. We present the DBBPLM algorithm, which trains with a dynamic function for each the learning rate and momentum factor.<br /> A Sigmoid function used as activation function. The XOR problem, balance, breast cancer and iris dataset were used as benchmarks for testing the effects of the dynamic DBBPLM algorithm. All the experiments were performed on Matlab 2012 a. The stop training was determined ten power -5. From the experimental results, the DBBPLM algorithm provides superior performance in terms of training, and faster training with higher accuracy compared to the BBP algorithm and with existing works.</span>

scholarly journals ArTSchives: un tremplin vers divers types de musées et vers la création artistique

2016 ◽  
Vol 43 (1) ◽  
pp. 90
Author(s):  
Lise Robichaud
Keyword(s):  
Cultural Context ◽  
Visual Art ◽  
Teaching Model ◽  
Art Appreciation ◽  
Human Sciences ◽  
Artistic Creation ◽  
Art Teaching ◽  
Museum Archives ◽  
Sciences Humaines ◽  
Analyse De Contenu

Abstract: The article introduces arTSchives, a visual art teaching model that integrates the concepts of museum, archives, and experiential learning. Its purpose is to help understand contemporary artwork of the archival type while proposing artistic creation channels that integrate the concept of archives. The author conducted a content analysis of visual art installations that resulted in a list of potential archive sources. This particular type of teaching promotes the visiting of contemporary art museums as well as natural sciences, human sciences and other types of specialised museums.KEYWORDS: Contemporary; museums; teaching model; Acadian cultural context; art appreciation; archival art; artistic creation; art galleryRésumé: L’article présente un modèle d’enseignement des arts visuels intitulé arTSchives qui intègre les notions de musée, d’archives et d’apprentissage expérientiel. Le but est de faciliter la compréhension des œuvres d’art contemporain de genre archivistique tout en proposant des pistes de création artistique intégrant le concept d’archives. L’auteure a procédé par une analyse de contenu d’installations en arts visuels ce qui a mené à l’énumération d’une liste d’exemples de sources d’archives possibles. Ce type particulier d’enseignement encourage la fréquentation des musées d’art contemporain ainsi que des musées de sciences naturelles, sciences humaines et autres musées spécialisés.MOTS CLES: Contemporain; musées; modèle d’enseignement; contexte culturel acadien; appréciation artistique; art archivistique

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