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Two Minute Papers · 发布于 2015年11月7日
This technique is a combination of two powerful machine learning algorithms: - convolutional neural networks are excellent at image classification, i.e., finding out what is seen on an input image, - recurrent neural networks that are capable of processing a sequence of inputs and outputs, therefore it can create sentences of what is seen on the image. Combining these two techniques makes it possible for a computer to describe in a sentence what is seen on an input image. _____________________ The paper "Deep Visual-Semantic Alignments for Generating Image Descriptions" is available here: http://cs.stanford.edu/people/karpathy/deepimagesent/ A gallery with more results with the same algorithm: http://cs.stanford.edu/people/karpathy/deepimagesent/generationdemo/ You can train your own convolutional neural network here: http://cs.stanford.edu/people/karpathy/convnetjs/demo/cifar10.html The source code for the project is now available here: https://github.com/karpathy/neuraltalk2 Subscribe if you would like to see more of these! - http://www.youtube.com/subscription_center?add_user=keeroyz The thumbnail image background was made by Georgie Pauwels (CC BY 2.0) - https://flic.kr/p/qrRciQ Splash screen/thumbnail design: Felícia Fehér - http://felicia.hu Károly Zsolnai-Fehér's links: Patreon → https://www.patreon.com/TwoMinutePapers Facebook → https://www.facebook.com/TwoMinutePapers/ Twitter → https://twitter.com/karoly_zsolnai Web → https://cg.tuwien.ac.at/~zsolnai/
