Draft:Darknet (software)

Darknet
Original author(s)Joseph Redmon
Initial releaseFirst Commit / November 4, 2013; 10 years ago (2013-11-04)
Repositorygithub.com/pjreddie/darknet
Written inC_language, CUDA
PlatformLinux, GNU_variants
Typemachine learning and deep learning
LicenseMETA-LICENSE, GPL Version 3 or any later version, YOLO LICENSE, MIT_License
Websitehttps://pjreddie.com/darknet/

Darknet

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Darknet[1][2] is a free and open-source artificial intelligence program, written in C and CUDA, made to do things like "You only look once" scanning,[3][4][5][6][7][8][9] image manipulation,[10] playing the board game Go,[11] Recurrent neural networks,[12][7] image classification,[13] and may be programmed to do other things.

You only look once algorithm

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Image manipulation AI part

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Go game AI part

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Recurrent neural networks AI part

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Computer_vision part

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Other notably uses of Darknet

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Websites showing information about darknet

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This program can be found in the packages of Trisquel GNU/Linux,[14] PureOS,[15] as well as compiled from source code.

A webpage was made at MathWorks's website about this program.[16]

There is a webpage at medium.com showing blood cell detection using darknet.[17]

libexplainer.com has an article about how darknet is used by organizations such as YOLO and OpenCV.[18]

OpenCV has shown darknet as a supported framework for its OpenCV program.[19]

References

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  1. ^ "Darknet: Open Source Neural Networks in C". 18 December 2023. Archived from the original on 18 December 2023. Retrieved 18 December 2023.
  2. ^ "darknet". GitHub. 18 December 2023. Archived from the original on 18 December 2023. Retrieved 18 December 2023.
  3. ^ "YOLO: Real-Time Object Detection". 19 December 2023. Archived from the original on 19 December 2023. Retrieved 19 December 2023.
  4. ^ "Understanding a Real-Time Object Detection Network: You Only Look Once (YOLOv1)". 19 December 2023. Archived from the original on 20 December 2023. Retrieved 20 December 2023.
  5. ^ "how to use darknet to train your own neural network". 20 December 2023. Archived from the original on 20 December 2023. Retrieved 20 December 2023.
  6. ^ "How computers learn to recognize objects instantly". 20 December 2023. Archived from the original on 20 December 2023. Retrieved 20 December 2023.
  7. ^ a b "Darknet: The Open Source Framework for Deep Neural Networks". 20 December 2023. Archived from the original on 20 December 2023. Retrieved 20 December 2023.
  8. ^ "Your Comprehensive Guide to the YOLO Family of Models". 21 December 2023. Archived from the original on 21 December 2023. Retrieved 21 December 2023.
  9. ^ "People's Choice Award at CVPR 2016". 21 December 2023. Archived from the original on 21 December 2023. Retrieved 21 December 2023.
  10. ^ "Nightmare". 19 December 2023. Archived from the original on 19 December 2023. Retrieved 19 December 2023.
  11. ^ "DarkGo: Go in Darknet". 18 December 2023. Archived from the original on 19 December 2023. Retrieved 19 December 2023.
  12. ^ "RNNs in Darknet". 19 December 2023. Archived from the original on 19 December 2023. Retrieved 19 December 2023.
  13. ^ "ImageNet Classification". 18 December 2023. Archived from the original on 19 December 2023. Retrieved 19 December 2023.
  14. ^ "RPackage: darknet (0.0.0+git20180914.61c9d02e-2build4)". 19 December 2023. Archived from the original on 19 December 2023. Retrieved 19 December 2023.
  15. ^ "Index of /pureos/pool/main/d/darknet/)". 19 December 2023. Archived from the original on 19 December 2023. Retrieved 19 December 2023.
  16. ^ "yolov3-yolov4-matlab". 19 December 2023. Archived from the original on 19 December 2023. Retrieved 19 December 2023.
  17. ^ "Blood Cells Detection with YOLOV3 Darknet". 20 December 2023. Archived from the original on 20 December 2023. Retrieved 20 December 2023.
  18. ^ "darknet Convolutional Neural Networks". 20 December 2023. Archived from the original on 20 December 2023. Retrieved 20 December 2023.
  19. ^ "Deep Learning in OpenCV". GitHub. 14 July 2019. Archived from the original on 14 July 2019. Retrieved 14 July 2019.
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  • Website [1]
  • Git repository [2]
  • External source[3]