Tree-structured multi-stage principal component analysis (TMPCA): Theory and applications

Su, Yuanhang; Lin, Ruiyuan; Kuo, C.-C. Jay

doi:10.1016/j.eswa.2018.10.020

Cited by 26 publications

(14 citation statements)

References 27 publications

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“…Also, we use a linear regression model in this study and find many features are correlated. In our future work, we should apply a dimension reduction technique, such as PCA, to reduce dimensionality on the entire feature space [38,39].…”

Section: Discussionmentioning

confidence: 99%

Visual order of Chinese ink paintings

Fan

Zhang

2020

Vis. Comput. Ind. Biomed. Art

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Visual order is one of the key factors influencing the aesthetic judgment of artworks. This paper reports the results of evaluating the influence of extracted features on visual order in Chinese ink paintings, using a regression model. We use nine contemporary artists’ paintings as examples and extract features related to the visual order of their paintings. A questionnaire survey is conducted to collect people’s rating scores on the visual order. Via regression modeling, our research analyzes the significance of each feature and validates the influences of the features on the visual order.

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Section: Discussionmentioning

confidence: 99%

Visual order of Chinese ink paintings

Fan

Zhang

2020

Vis. Comput. Ind. Biomed. Art

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“…This analytical approach did better result and the accuracy was 85.23%. The tree-structured multi-linear principal component analysis (TMPCA) [41] proposed for text classification is a novel data processing technique. To facilitate the machine learning task that follows, the TMPCA can effectively decrease the size of the entire sentence data.…”

Section: Related Workmentioning

confidence: 99%

Public Sentiment Analysis on Twitter Data during COVID-19 Outbreak

Kausar¹,

Soosaimanickam²,

Nasar³

2021

IJACSA

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The COVID-19 pandemic, is also known as the coronavirus pandemic, is an ongoing serious global problem all over the world. The outbreak first came to light in December 2019 in Wuhan, China. This was declared pandemic by the World Health Organization on 11th March 2020. COVID-19 virus infected on people and killed hundreds of thousands of people in the United States, Brazil, Russia, India and several other countries. Since this pandemic continues to affect millions of lives, and a number of countries have resorted to either partial or full lockdown. People took social media platforms to share their emotions, and opinions during this lockdown to find a way to relax and calm down. In this research work, sentiment analysis on the tweets of people from top ten infected countries has been conducted. The experiments have been conducted on the collected data related to the tweets of people from top ten infected countries with the addition of one more country chosen from Gulf region, i.e.

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“…Besides, combining neural network architecture with other classification is done to reach maximum accuracy [5]. A hybrid approach using deep learning and other machine learning would be a good interest to reach better accuracy [50][51][52][53][54].…”

Section: Classification In Handwriting Analysismentioning

confidence: 99%

Automated handwriting analysis based on pattern recognition: a survey

Samsuryadi¹,

Kurniawan²,

Mohamad³

2021

IJEECS

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<span>Handwriting analysis has wide scopes include recruitment, medical diagnosis, forensic, psychology, and human-computer interaction. Computerized handwriting analysis makes it easy to recognize human personality and can help graphologists to understand and identify it. The features of handwriting use as input to classify a person’s personality traits. This paper discusses a pattern recognition point of view, in which different stages are described. The stages of study are data collection and pre-processing technique, feature extraction with associated personality characteristics, and the classification model. Therefore, the purpose of this paper is to present a review of the methods and their achievements used in various stages of a pattern recognition system. </span>

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Tree-structured multi-stage principal component analysis (TMPCA): Theory and applications

Cited by 26 publications

References 27 publications

Visual order of Chinese ink paintings

Visual order of Chinese ink paintings

Public Sentiment Analysis on Twitter Data during COVID-19 Outbreak

Automated handwriting analysis based on pattern recognition: a survey

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