Deep Dream Visualization Clip

This is a video of Google Brain‘s Deep Dream computer vision as it attempts to recognize shapes within the input video.  The output video (shown) is really quite interesting to watch.  If you want to know how Deep Dream do what it do, click here for a general overview on how it works; very fascinating. 

Runtime: 5:36

This video can also be found here.

Video Info:

Published on Jul 7, 2015

A journey through all the layers of an artificial neural network.

This video is made using a visualization technique applied to a neural network trained to recognize a broad range of images. Each frame is recursively fed back to the network starting with a frame of random noise. Every 100 frames (4 seconds) the next layer is targeted until the lowest layer is reached.

Based on the work by Google researchers Alexander Mordvintsev, Christopher Olah and Mike Tyka. See for more information.”
~Johan Nordberg, original video creator.

Original video by Johan Nordberg here.

special thanks to Ektoplazm for inspiration
Music: Journey on the Sunset by Sam’adhi on the Low Tide VA…

How Google’s Deep Dream Works

The following video is a general description of how Google’s Deep Dream computer vision (image recognition) works.  Deep Dream uses a convolutional neural network to look for patterns in an image or video based on large sets of images previously analyzed for defining characteristics.  The beauty of Deep Dream is that it can modify images to accent fragments within the image to more closely resemble the aspects from images it has previously evaluated.  The effects of such augmentation can be quite striking; creating strange, almost psychedelic, results.

Runtime: 13:42

This video can also be found here.

Video Info:

Published on Aug 26, 2016

Surreal images created by Google’s Deep Dream code flooded the internet in 2015 but how does deep dream do it? Image analyst Dr Mike Pound.

Inside a Neural Network:
Cookie Stealing:
FPS & Digital Video:
Password Cracking:
Gamer’s Paradise:

Images seen/manipulated in this video:…

This video was filmed and edited by Sean Riley.

Computer Science at the University of Nottingham:

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