Assessing the best art design based on artificial intelligence and machine learning using GTMA

• Published in: Soft computing (Berlin, Germany) Vol. 27; no. 1; pp. 149 - 156
• Main Authors: Wenjing, Xu, Cai, Zilu
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 2023
• Subjects: Artificial Intelligence; Computational Intelligence; Control; Engineering; Fuzzy Systems and Their Mathematics; Mathematical Logic and Foundations; Mechatronics; Robotics; Art design; Sentiments; Artificial intelligence; Emotions; Machine learning
• ISSN: 1432-7643; 1433-7479
• DOI: 10.1007/s00500-022-07555-1

Art, like language, is a method for expressing a person's thoughts and opinions to others. Art design is a way of conveying human sentiments and emotions, particularly via the use of visual structures such as paintings or drawings. Every element of our lives, including arts and crafts, has been favorably influenced by the introduction of innovative technologies such as artificial intelligence (AI) and deep learning (DL). In today's modern era, the technologies have revolutionized the way art is created, consumed, and distributed. Machine learning and human emotions are the two most important aspects of interactive and high-quality art design. In the teaching and learning of art-related courses, AI and machine learning are used to develop students' creative talents more successfully than traditional learning methods. With the use of information technology, designers build and design more productive artwork in very little time and with much less effort. In the evolution and creation of interactive and intelligent digital art, artificial intelligence and machine learning are playing a highly positive role. Art developed with the use of these approaches is capable of conveying human emotions and sentiments precisely and correctly. The proposed study presents a comprehensive overview of various AI-grounded smart and intelligent applications employed for the betterment and development of art design. The study provided a summary of the existing approaches used in the area of art design for the designing of high-quality and precise artwork. Then, based on the proposed overview, various features are extracted from the existing literature. From these extracted features, important features were selected for the decision-making procedure and ranking. To perform the decision-making process for the ranking of the accessible alternatives, the Graph Theory Matrix Approach was applied. The results of the study show effectiveness of the AI-based systems for art design.