Generation of realistic images from human drawn sketches using deep learning
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022.
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| التنسيق: | أطروحة |
| اللغة: | English |
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Brac University
2022
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| الموضوعات: | |
| الوصول للمادة أونلاين: | http://hdl.handle.net/10361/16818 |
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10361-16818 |
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10361-168182022-06-01T21:01:59Z Generation of realistic images from human drawn sketches using deep learning Mahbub, Mohammed Julfikar Ali Rahmatullah, S. Afsan Rahman, G M Sohanur Zillanee, Abu Hasnayen Akib, Aknur Kamal Alam, Md. Ashraful Department of Computer Science and Engineering, Brac University GAN Sketch to realistic image Data augmentation Diversity of domain Cognitive learning theory (Deep learning) Artificial intelligence This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022. Cataloged from PDF version of thesis. Includes bibliographical references (pages 23-26). Processing sketches to produce realistic images is an intriguing idea in the world of emerging Artificial Intelligence. We present a Generative Adversarial Network (GAN) based methodology that creates satisfactory images for the most prevalent categories in our approach. The proposed approach is applicable not just to people, but also to animals, objects and foods. The system takes a sketch and analyzes it using a powerful neural engine to produce new photographs that resemble realistic images. We also used a data augmentation method to dramatically increase the variety of data available for training models. The proposed model has achieved approximately 96.36% accuracy over generating sketch to realistic images of people and 40.63% accuracy for objects and animals. Moreover, about 76.63% accuracy on generating sketches from strokes on an average from people class. Mohammed Julfikar Ali Mahbub S. Afsan Rahmatullah G M Sohanur Rahman Abu Hasnayen Zillanee Aknur Kamal Akib B. Computer Science 2022-06-01T09:28:11Z 2022-06-01T09:28:11Z 2022 2022-01 Thesis ID 21341031 ID 21241075 ID 21341049 ID 18301159 ID 18301209 http://hdl.handle.net/10361/16818 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 26 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
GAN Sketch to realistic image Data augmentation Diversity of domain Cognitive learning theory (Deep learning) Artificial intelligence |
| spellingShingle |
GAN Sketch to realistic image Data augmentation Diversity of domain Cognitive learning theory (Deep learning) Artificial intelligence Mahbub, Mohammed Julfikar Ali Rahmatullah, S. Afsan Rahman, G M Sohanur Zillanee, Abu Hasnayen Akib, Aknur Kamal Generation of realistic images from human drawn sketches using deep learning |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022. |
| author2 |
Alam, Md. Ashraful |
| author_facet |
Alam, Md. Ashraful Mahbub, Mohammed Julfikar Ali Rahmatullah, S. Afsan Rahman, G M Sohanur Zillanee, Abu Hasnayen Akib, Aknur Kamal |
| format |
Thesis |
| author |
Mahbub, Mohammed Julfikar Ali Rahmatullah, S. Afsan Rahman, G M Sohanur Zillanee, Abu Hasnayen Akib, Aknur Kamal |
| author_sort |
Mahbub, Mohammed Julfikar Ali |
| title |
Generation of realistic images from human drawn sketches using deep learning |
| title_short |
Generation of realistic images from human drawn sketches using deep learning |
| title_full |
Generation of realistic images from human drawn sketches using deep learning |
| title_fullStr |
Generation of realistic images from human drawn sketches using deep learning |
| title_full_unstemmed |
Generation of realistic images from human drawn sketches using deep learning |
| title_sort |
generation of realistic images from human drawn sketches using deep learning |
| publisher |
Brac University |
| publishDate |
2022 |
| url |
http://hdl.handle.net/10361/16818 |
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| _version_ |
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