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File:Simplified neural network example.svg

From Wikipedia, the free encyclopedia

Original file(SVG file, nominally 1,028 × 882 pixels, file size: 71 KB)

Summary

Description
Simplified neural network example for object detection: As seen at the output at right, the network is trained to associate a ringed texture and star outline with a starfish, and a striped texture and oval shape with a sea urchin. In this run, it correctly detects the starfish in the input picture at left. In addition, a shell that was not included in the training gives a weak signal for the oval shape, resulting in a weak signal from only one of two intermediate nodes for the sea urchin output, which may still result in a false positive result (or "hallucination") for sea urchin. In reality, textures and outlines would not be represented by single nodes, but rather by associated weight patterns of multiple nodes.
Date
Source

Own work

  • Reference: Ferrie, C., & Kaiser, S. (2019) Neural Networks for Babies, Sourcebooks ISBN: 1492671207.
Author
Mikael Häggström, M.D. Author info
- Reusing images
- Conflicts of interest:
  None
Mikael Häggström, M.D.
Other versions
Raster (.png) version

Context

Simplified example of training a neural network in object detection: The network is trained by multiple images that are known to depict starfish and sea urchins, which are correlated with "nodes" that represent visual features. The starfish match with a ringed texture and a star outline, whereas most sea urchins match with a striped texture and oval shape. However, the instance of a ring textured sea urchin creates a weakly weighted association between them.
Subsequent run of the network on an input image (left): The network correctly detects the starfish. However, the weakly weighted association between ringed texture and sea urchin also confers a weak signal to the latter from one of two intermediate nodes. In addition, a shell that was not included in the training gives a weak signal for the oval shape, also resulting in a weak signal for the sea urchin output. These weak signals may result in a false positive result for sea urchin.


Licensing

Creative Commons CC-Zero This file is made available under the Creative Commons CC0 1.0 Universal Public Domain Dedication.
The person who associated a work with this deed has dedicated the work to the public domain by waiving all of their rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law. You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission.

Captions

Simplified neural network example: The network is trained to associate a ringed pattern and star outline with a sea star, and a striped pattern and oval shape with a sea urchin. In this run, it correctly detects the sea star in the picture at left.

Items portrayed in this file

depicts

21 September 2023

File history

Click on a date/time to view the file as it appeared at that time.

Date/TimeThumbnailDimensionsUserComment
current21:52, 2 October 2023Thumbnail for version as of 21:52, 2 October 20231,028 × 882 (71 KB)Mikael HäggströmUpdate
05:51, 22 September 2023Thumbnail for version as of 05:51, 22 September 20231,028 × 882 (66 KB)Mikael HäggströmMinor correction
05:49, 22 September 2023Thumbnail for version as of 05:49, 22 September 20231,028 × 882 (66 KB)Mikael HäggströmLess overlapping
09:58, 21 September 2023Thumbnail for version as of 09:58, 21 September 20231,028 × 882 (64 KB)Mikael HäggströmArrows from circle borders
09:53, 21 September 2023Thumbnail for version as of 09:53, 21 September 20231,028 × 882 (64 KB)Mikael HäggströmAdjustment
06:12, 21 September 2023Thumbnail for version as of 06:12, 21 September 20231,028 × 882 (110 KB)Mikael HäggströmUploaded a work by {{Mikael Häggström|cat=Non-medical diagrams}} from {{Own}} with UploadWizard

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