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Classification and Evaluation of Free-Hand Sketches Using Image Processing and Deep Learning Techniques
Md. Afzalur Rahaman, Fahima Hossain, Hasan Mahmud, Mahdi Hassan Sabbir, Md. Masud Hasan
Pages - 1 - 16     |    Revised - 28-02-2023     |    Published - 01-04-2023
Volume - 12   Issue - 1    |    Publication Date - April 2023  Table of Contents
Deep Learning, Freehand Sketch Evaluation, Image Processing, Multi-labeled CNN.
Evaluation is a crucial issue in a learning system. Instructors frequently assign a collection of questions, which students must respond to in the script, in order to evaluate their performance. An answer is most often composed of text, equations, and figures. The sketched figures must be recognized and rated according to their actual appearance. With the advancement of computer vision, several methods have been developed for recognizing and grading handwritten text accurately. To ensure a fair automatic evaluation system, we must develop a system that can grade text and images simultaneously. Due to the complex structure of images, we need to extract important features in the image, unlike traditional text grading methods. The major focus of this research work is mostly on the freehand sketch phase, therefore developing a CNN model, that can classify and assign a grade to a given image automatically. The model is trained with a
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Mr. Md. Afzalur Rahaman
Computer Science and Engineering, Hamdard University Bangladesh, Munshiganj-1510 - Bangladesh
Miss Fahima Hossain
Computer Science and Engineering, Hamdard University Bangladesh, Munshiganj-1510 - Bangladesh
Mr. Hasan Mahmud
Computer Science and Engineering, Hamdard University Bangladesh, Munshiganj-1510 - Bangladesh
Mr. Mahdi Hassan Sabbir
Computer Science and Engineering, Hamdard University Bangladesh, Munshiganj-1510 - Bangladesh
Mr. Md. Masud Hasan
Computer Science and Engineering, Hamdard University Bangladesh, Munshiganj-1510 - Bangladesh

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