Author
Aditya Chitlangia
Bio: Aditya Chitlangia is an academic researcher from VIT University. The author has contributed to research in topics: Graphology & Handwriting. The author has an hindex of 1, co-authored 1 publications receiving 4 citations.
Topics: Graphology, Handwriting
Papers
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TL;DR: A computerized method for personality trait prediction based on the users handwriting is proposed and predicts the personality trait of a person with 80% correctness using the Polynomial kernel.
18 citations
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TL;DR: In this article, a random patches-based edge-preserving network (RPEP) was proposed for polarimetric synthetic aperture radar (PolSAR) image classification, where an initial spatial feature extraction is performed by using a Gaussian distribution.
Abstract: A random patches-based edge-preserving network (RPEP) is proposed for polarimetric synthetic aperture radar (PolSAR) image classification in this paper. An initial spatial feature extraction is fir...
10 citations
7 citations
TL;DR: 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, in which different stages are described.
Abstract: 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
7 citations
5 citations
DOI•
06 Oct 2021
TL;DR: In this article, a basic personality test was applied to the users who voluntarily participated in the study, some distinctive writing characteristics were extracted from the text samples taken from the same users, and machine learning-based prediction models were developed based on the features constructed over these font characteristics.
Abstract: In the field of graphology, the fundamental idea is to establish a connection between the handwriting style of people and their personality traits. In this study, an analysis was made on the science of graphology using machine learning and psychology. A basic personality test was applied to the users who voluntarily participated in our study, some distinctive writing characteristics were extracted from the text samples taken from the same users, and machine learning-based prediction models were developed based on the features constructed over these font characteristics. Here, the aim is to examine how successful matching can be implemented automatically from the user's writing style with regard to personality analysis. The results show that even though not very sensitive, the personality traits can be predicted to a certain extent from the writing style by the machine learning models.
1 citations