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Research Article
Tinker Hunt
Shubham Gulia1
Anshika Agrawal2
Harsh Jain3
Dr. Ankita Gupta4
123 Department of Computer Science & Engineering, Maharaja Agrasen Institute Of Technology , India. 4Supervisor, Department of Computer Science & Engineering, Maharaja Agrasen Institute of Technology, India.
Published Online: May-June 2023
Pages: 492-495
Cite this article
↗ https://www.doi.org/10.59256/ijire.20230403117
References
1. Ha, D., & Eck, D. (2017). A neural representation of sketch draw- ings. arXiv preprint arXiv:1704.03477.
2. Habibollah Agh Atabay, “Hand Drawn Sketch Classification Using Convolutional Neural Networks”, Gonbad Kavous
University, Iran, 2016.
3. E. Boyaci and M. Sert, "Feature-level fusion of deep convolutional neural networks for sketch recognition on smartphones," 2017
IEEE International Conference on Consumer Electronics (ICCE), Las Vegas, NV, 2017.
4. Wayne Lu, Elizabeth Tran, “Free-hand Sketch Recognition Classification”, Stanford University, 2017.
5. Kristine Guo, James WoMa, Eric Xu, “Quick, Draw! Doodle Recognition” Stanford University, 2018.
6. A Comprehensive Guide to Convolutional Neural Networks — the ELI5 way.
7. Meta Analysis of Deep Learning Models for Doodle Recognition.
8. Lu, W., & Tran, E. (2017). Free-hand Sketch Recognition Classifi-cation.
9. Rui Hu and John Collomosse. 2013. A performance evaluation of gradient field hog descriptor for sketch based image retrieval.
Computer Vision and Image Understanding 117, 7 (2013), 790ś806.
10. Forrest Huang, John F. Canny, and Jeffrey Nichols. 2019. Swire: Sketch-based user interface retrieval. In Proceedings of the 2019
CHI Conference on Human Factors in Computing Systems. ACM.
11. Alex Krizhevsky, Ilya Sutskever, and Geoffrey E.Hinton. 2012. ImageNet classification with deep convolutional neural networks. In
Proc. 26th Annual Conference on Neural Information Processing Systems (NIPS). NIPS, 1106ś1114.
12. Jonas Jongejan, Henry Rowley, Takashi Kawashima, Jongmin Kim, and Nick Fox-Gieg. 2016. Quick, Draw!
https://quickdraw.withgoogle.com/ Accessed March 2022.
2. Habibollah Agh Atabay, “Hand Drawn Sketch Classification Using Convolutional Neural Networks”, Gonbad Kavous
University, Iran, 2016.
3. E. Boyaci and M. Sert, "Feature-level fusion of deep convolutional neural networks for sketch recognition on smartphones," 2017
IEEE International Conference on Consumer Electronics (ICCE), Las Vegas, NV, 2017.
4. Wayne Lu, Elizabeth Tran, “Free-hand Sketch Recognition Classification”, Stanford University, 2017.
5. Kristine Guo, James WoMa, Eric Xu, “Quick, Draw! Doodle Recognition” Stanford University, 2018.
6. A Comprehensive Guide to Convolutional Neural Networks — the ELI5 way.
7. Meta Analysis of Deep Learning Models for Doodle Recognition.
8. Lu, W., & Tran, E. (2017). Free-hand Sketch Recognition Classifi-cation.
9. Rui Hu and John Collomosse. 2013. A performance evaluation of gradient field hog descriptor for sketch based image retrieval.
Computer Vision and Image Understanding 117, 7 (2013), 790ś806.
10. Forrest Huang, John F. Canny, and Jeffrey Nichols. 2019. Swire: Sketch-based user interface retrieval. In Proceedings of the 2019
CHI Conference on Human Factors in Computing Systems. ACM.
11. Alex Krizhevsky, Ilya Sutskever, and Geoffrey E.Hinton. 2012. ImageNet classification with deep convolutional neural networks. In
Proc. 26th Annual Conference on Neural Information Processing Systems (NIPS). NIPS, 1106ś1114.
12. Jonas Jongejan, Henry Rowley, Takashi Kawashima, Jongmin Kim, and Nick Fox-Gieg. 2016. Quick, Draw!
https://quickdraw.withgoogle.com/ Accessed March 2022.
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