From Classification to Regression: Model Transfer for Visual Aesthetic Quality Assessment

2017 ◽  
Author(s):  
Wenzhen Huang ◽  
Peipei Yang ◽  
Kaiqi Huang
Keyword(s):  
Regression Model ◽  
Quality Assessment ◽  
Aesthetic Quality ◽  
Model Transfer

scholarly journals Product Design Award Prediction Modeling: Design Visual Aesthetic Quality Assessment via DCNNs

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 211028-211047
Author(s):  
Jianfeng Wu ◽  
Baixi Xing ◽  
Huahao Si ◽  
Jian Dou ◽  
Jin Wang ◽  
...  
Keyword(s):  
Quality Assessment ◽  
Product Design ◽  
Prediction Modeling ◽  
Aesthetic Quality

scholarly journals Video Aesthetic Quality Assessment by Temporal Integration of Photo- and Motion-Based Features

2013 ◽  
Vol 15 (8) ◽  
pp. 1944-1957 ◽  
Author(s):  
Hsin-Ho Yeh ◽  
Chun-Yu Yang ◽  
Ming-Sui Lee ◽  
Chu-Song Chen
Keyword(s):  
Quality Assessment ◽  
Temporal Integration ◽  
Aesthetic Quality

scholarly journals Two open-source projects for image aesthetic quality assessment

2018 ◽  
Vol 62 (2) ◽  
Author(s):  
Le Wu ◽  
Xin Jin ◽  
Geng Zhao ◽  
Xinghui Zhou
Keyword(s):  
Quality Assessment ◽  
Open Source ◽  
Aesthetic Quality

scholarly journals Urban Air Quality Assessment Using Integrated Artificial Intelligence Algorithms and Geographic Information System Modeling in a Highly Congested Area, Iraq

2020 ◽  
Vol 55 (1) ◽  
Author(s):  
Oday Zakariya Jasim ◽  
Noor Hashim Hamed ◽  
Mohammed Abdullah Abid
Keyword(s):  
Information System ◽  
Air Quality ◽  
Geographic Information System ◽  
Regression Model ◽  
Quality Assessment ◽  
Urban Areas ◽  
Geographic Information ◽  
Urban Air ◽  
Congested Area ◽  
Air Quality Assessment

Pollutant emissions are considered to be a major threat to air quality and human health in urban areas. Therefore, accurate modeling and assessment tools are required. In this study, a model was done by the integration of machine learning algorithms and a geographic information system model. This model included the optimization of the support vector regression model by using the principal component analysis algorithm. Then, the integration of the regression model with spatial analysis modeling via a grid (100 x 100 m) was done in order to generate prediction maps during holidays and workdays in the daytime and at nighttime in a highly congested area in Baghdad city, Iraq. The data used in this study categorized into two categories. The first category is the data acquired through field surveying that includes temperature, humidity, wind speed, wind direction, and traffic flow data (e.g., the number of light and heavy vehicles), as well as carbon monoxide samples by using mobile equipment. The second category is the information derived from geographic information system data, such as land use, road network, and building height. The accuracy of the proposed model is 81%, and the lowest value of root mean square error was 0.067 ppm. The integration between air pollution models and geographic information system techniques could be a promising tool for urban air quality assessment and urban planning. These tools effectively utilized by stakeholders and decision-makers to outline proper plans and strategies to mitigate air pollutants in urban areas.

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