Journal Article

·2017

Identification and seperation of Turkish and Australian cartoons by wavelet transform and neural networks methods

Bahadır UÇAN YTU , Mehmet Emin Kahraman YTU

Abstract

Art and science show progress together and they are one of the most important parameters indicating development levels of countries, nations and societies. Moreover, art generates new concepts, environments and tools with the contributions of science and technology. Cartoon as an art discipline, as for all other fields of art, needs to be defined through new approaches such as Wavelet Transform and Neural Networks Methods which are commonly being used in image processing, compression, classification in various medical and biomedical fields. In this study, it is planned to apply such digital and analytical methods on Turkish and Australian cartoon data. Due to parallelism on drawing styles and characteristics of same periods' or following periods' cartoons of artists; physical classification and separation of cartoons may become harder. In addition, criticisms on cartoons commonly are to be interpretative without exact analytical indicators.

Keywords

Turkish Wavelet transform Computer science Artificial neural network Wavelet Artificial intelligence Identification (biology) Data science Pattern recognition (psychology) Linguistics

Subject Areas

Advanced Image and Video Retrieval Techniques ·Computer Vision and Pattern Recognition ·Physical Sciences
Cultural and Sociopolitical Studies ·Museology ·Social Sciences

OpenAlex SDG Match

SDGs auto-classified by OpenAlex (score ≥ 0.4 shown).

Partnerships for the goals 47%