DeepDream

DeepDream je program za računarski vid kreiran od strane Guglovih inženjera Aleksandra Mordvinceva koji koristi konvolucionu neuronsku mrežu da pronađe i poboljša paterne na slikama putem algoritamske pareidolije, stvarajući tako izgled nalik snu koji podseća na psihodelično iskustvo u namerno prerađenim slikama.^[1]^[2]^[3]

Guglov program je popularizovao termin (duboko) „sanjanje“ da se odnosi na generisanje slika koje proizvode željene aktivacije u obučenoj dubokoj mreži, a termin se sada odnosi na kolekciju srodnih pristupa.

Istorija

Softver DeepDream, nastao u dubokoj konvolucionoj mreži pod kodnim imenom „Inception“ po istoimenom filmu,^[1]^[2]^[3] je razvijen za ImageNet veliki izazov vizuelnog prepoznavanja (ILSVRC) 2014. godine^[3] i objavljen u julu 2015.

Ideja i ime iz snova postali su popularni na internetu 2015. zahvaljujući Guglovom programu Dipdrim. Ideja datira iz rane istorije neuronskih mreža,^[4] i slične metode su korišćene za sintezu vizuelnih tekstura.^[5] Srodne ideje za vizuelizaciju razvilo je (pre Guglovog rada) nekoliko istraživačkih grupa.^[6]^[7]

Nakon što je Gugl objavio svoje tehnike i učinio svoj kod otvorenim kodom,^[8] na tržištu su se pojavili brojni alati u obliku veb servisa, mobilnih aplikacija i desktop softvera koji omogućavaju korisnicima da transformišu sopstvene fotografije.^[9]

Reference

^ ^а ^б Mordvintsev, Alexander; Olah, Christopher; Tyka, Mike (2015). „DeepDream - a code example for visualizing Neural Networks”. Google Research. Архивирано из оригинала 2015-07-08. г.
^ ^а ^б Mordvintsev, Alexander; Olah, Christopher; Tyka, Mike (2015). „Inceptionism: Going Deeper into Neural Networks”. Google Research. Архивирано из оригинала 2015-07-03. г.
^ ^а ^б ^в Szegedy, Christian; Liu, Wei; Jia, Yangqing; Sermanet, Pierre; Reed, Scott E.; Anguelov, Dragomir; Erhan, Dumitru; Vanhoucke, Vincent; Rabinovich, Andrew (2015). „Going deeper with convolutions”. IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015, Boston, MA, USA, June 7–12, 2015. IEEE Computer Society. стр. 1—9. arXiv:1409.4842 . doi:10.1109/CVPR.2015.7298594.
^ Lewis, J.P. (1988). „Creation by refinement: a creativity paradigm for gradient descent learning networks”. IEEE International Conference on Neural Networks. IEEE International Conference on Neural Networks. стр. 229—233 vol.2. ISBN 0-7803-0999-5. doi:10.1109/ICNN.1988.23933.
^ Portilla, J; Simoncelli, Eero (2000). „A parametric texture model based on joint statistics of complex wavelet coefficients”. International Journal of Computer Vision. 40: 49—70. S2CID 2475577. doi:10.1023/A:1026553619983.
^ Erhan, Dumitru. (2009). Visualizing Higher-Layer Features of a Deep Network. International Conference on Machine Learning Workshop on Learning Feature Hierarchies. S2CID 15127402.
^ Simonyan, Karen; Vedaldi, Andrea; Zisserman, Andrew (2014). Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps. International Conference on Learning Representations Workshop. arXiv:1312.6034 .
^ deepdream на веб-сајту GitHub
^ Daniel Culpan (2015-07-03). „These Google "Deep Dream" Images Are Weirdly Mesmerising”. Wired. Архивирано из оригинала 08. 05. 2016. г. Приступљено 2015-07-25.

Spoljašnje veze

Deep Dream, python notebook na veb-sajtu GitHub
Mordvintsev, Alexander; Olah, Christopher; Tyka, Mike (17. 6. 2015). „Inceptionism: Going Deeper into Neural Networks”. Архивирано из оригинала 2015-07-03. г.

[codexample-1] а ^б Mordvintsev, Alexander; Olah, Christopher; Tyka, Mike (2015). „DeepDream - a code example for visualizing Neural Networks”. Google Research. Архивирано из оригинала 2015-07-08. г.

[goingdeeper-2] а ^б Mordvintsev, Alexander; Olah, Christopher; Tyka, Mike (2015). „Inceptionism: Going Deeper into Neural Networks”. Google Research. Архивирано из оригинала 2015-07-03. г.

[arxiv-3] а ^б ^в Szegedy, Christian; Liu, Wei; Jia, Yangqing; Sermanet, Pierre; Reed, Scott E.; Anguelov, Dragomir; Erhan, Dumitru; Vanhoucke, Vincent; Rabinovich, Andrew (2015). „Going deeper with convolutions”. IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015, Boston, MA, USA, June 7–12, 2015. IEEE Computer Society. стр. 1—9. arXiv:1409.4842 . doi:10.1109/CVPR.2015.7298594.

[lewis88-4] Lewis, J.P. (1988). „Creation by refinement: a creativity paradigm for gradient descent learning networks”. IEEE International Conference on Neural Networks. IEEE International Conference on Neural Networks. стр. 229—233 vol.2. ISBN 0-7803-0999-5. doi:10.1109/ICNN.1988.23933.

[portilla00-5] Portilla, J; Simoncelli, Eero (2000). „A parametric texture model based on joint statistics of complex wavelet coefficients”. International Journal of Computer Vision. 40: 49—70. S2CID 2475577. doi:10.1023/A:1026553619983.

[erhan09-6] Erhan, Dumitru. (2009). Visualizing Higher-Layer Features of a Deep Network. International Conference on Machine Learning Workshop on Learning Feature Hierarchies. S2CID 15127402.

[simonyan14-7] Simonyan, Karen; Vedaldi, Andrea; Zisserman, Andrew (2014). Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps. International Conference on Learning Representations Workshop. arXiv:1312.6034 .

[github-8] ream на веб-сајту GitHub

[9] Daniel Culpan (2015-07-03). „These Google "Deep Dream" Images Are Weirdly Mesmerising”. Wired. Архивирано из оригинала 08. 05. 2016. г. Приступљено 2015-07-25.

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