Research Article
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Snake Detection and Blurring System to Prevent Unexpected Appearance of Snake Images on Visual Media Sources Using Deep Learning

Year 2021, Volume: 1 Issue: 2, 125 - 135, 30.12.2021
https://izlik.org/JA84SY77MM

Abstract

This paper proposes an object detection and blurring system using deep learning especially for the detection of snake images since while some of the people does not care about the appearance of the snake images on the visual sources, there is a significant portion of them who are uncomfortable of seeing snakes as well as their images. Therefore, with the system that is proposed in this paper, the snake objects from the images would be detected with YOLOv4 trained model and blurred using OpenCV. The detection f1 score of the selected model is 92% on the test set.

References

  • [1] E. Landova, J. Maresova, O. Simkova, V. Cikanova and D. Frynta, "Human responses to live snakes and their photographs: Evaluation of beauty and fear of the king snakes," Journal of Environmental Psychology, vol. 32, no. 1, pp. 69-77, 3 2012.
  • [2] A. Bochkovskiy, C.-Y. Wang and H.-Y. M. Liao, "YOLOv4: Optimal Speed and Accuracy of Object Detection," 2020.
  • [3] M. Tan, R. Pang and Q. V. Le, "EfficientDet: Scalable and Efficient Object Detection," 2020.
  • [4] OpenCV team, "About," OpenCV, 2021. [Online]. Available: https://opencv.org/about/. [Accessed 20 May 2021].
  • [5] Google Inc., "Open Images V6 Snake Category Detection Type," 2021. [Online]. Available: https://storage.googleapis.com/openimages/web/visualizer/index.html?set=train&type=detection&c=%2Fm%2F078jl. [Accessed 20 May 2021].
  • [6] Google Inc., "Overview of Open Images V6," Google Inc., 2021. [Online]. Available: https://storage.googleapis.com/openimages/web/factsfigures.html. [Accessed 21 May 2021].
  • [7] AlexeyAB, "Yolo v4, v3 and v2 for Windows and Linux," 15 5 2021. [Online]. Available: https://github.com/AlexeyAB/darknet. [Accessed 21 May 2021].

Year 2021, Volume: 1 Issue: 2, 125 - 135, 30.12.2021
https://izlik.org/JA84SY77MM

Abstract

References

  • [1] E. Landova, J. Maresova, O. Simkova, V. Cikanova and D. Frynta, "Human responses to live snakes and their photographs: Evaluation of beauty and fear of the king snakes," Journal of Environmental Psychology, vol. 32, no. 1, pp. 69-77, 3 2012.
  • [2] A. Bochkovskiy, C.-Y. Wang and H.-Y. M. Liao, "YOLOv4: Optimal Speed and Accuracy of Object Detection," 2020.
  • [3] M. Tan, R. Pang and Q. V. Le, "EfficientDet: Scalable and Efficient Object Detection," 2020.
  • [4] OpenCV team, "About," OpenCV, 2021. [Online]. Available: https://opencv.org/about/. [Accessed 20 May 2021].
  • [5] Google Inc., "Open Images V6 Snake Category Detection Type," 2021. [Online]. Available: https://storage.googleapis.com/openimages/web/visualizer/index.html?set=train&type=detection&c=%2Fm%2F078jl. [Accessed 20 May 2021].
  • [6] Google Inc., "Overview of Open Images V6," Google Inc., 2021. [Online]. Available: https://storage.googleapis.com/openimages/web/factsfigures.html. [Accessed 21 May 2021].
  • [7] AlexeyAB, "Yolo v4, v3 and v2 for Windows and Linux," 15 5 2021. [Online]. Available: https://github.com/AlexeyAB/darknet. [Accessed 21 May 2021].
There are 7 citations in total.

Details

Primary Language English
Subjects Artificial Intelligence
Journal Section Research Article
Authors

Selay Tekgül This is me

Gökçe Nur Yılmaz

Submission Date November 23, 2021
Publication Date December 30, 2021
IZ https://izlik.org/JA84SY77MM
Published in Issue Year 2021 Volume: 1 Issue: 2

Cite

IEEE [1]S. Tekgül and G. Nur Yılmaz, “Snake Detection and Blurring System to Prevent Unexpected Appearance of Snake Images on Visual Media Sources Using Deep Learning”, Journal of Artificial Intelligence and Data Science, vol. 1, no. 2, pp. 125–135, Dec. 2021, [Online]. Available: https://izlik.org/JA84SY77MM

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