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Fayl:Simplified neural network example.svg

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English: 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.
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Oʻzimning ishim

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

  • Simplified example of training a neural network in object detection: The network is trained by multiple images known to depict starfish and sea urchins, which are correlated with "nodes" representing visual features. Starfish match with a ringed texture and star outline, whereas most sea urchins match with a striped texture and oval shape.
    Simplified example of training a neural network in object detection: The network is trained by multiple images known to depict starfish and sea urchins, which are correlated with "nodes" representing visual features. Starfish match with a ringed texture and star outline, whereas most sea urchins match with a striped texture and oval shape.
  • The resulting model contains weighted associations between visual features and output categories. Because one training image depicts a ring-textured sea urchin, the model also develops a weak association between ringed texture and sea urchin.
    The resulting model contains weighted associations between visual features and output categories. Because one training image depicts a ring-textured sea urchin, the model also develops a weak association between ringed texture and sea urchin.
  • Subsequent run of the model on an input image (left): The network correctly detects the starfish. However, the weak association between ringed texture and sea urchin also gives a weak signal to the latter from one of two intermediate nodes. In addition, a shell 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.
    Subsequent run of the model on an input image (left): The network correctly detects the starfish. However, the weak association between ringed texture and sea urchin also gives a weak signal to the latter from one of two intermediate nodes. In addition, a shell 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.

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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.

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tasvirlangan obyekt

TensorFlow

tashkil etilgan

21 sentyabr 2023

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joriy02:52, 2023-yil 3-oktyabr02:52, 2023-yil 3-oktyabr dagi versiya uchun tasvir1 028 × 882 (71 KB)wikimediacommons>Mikael HäggströmUpdate

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