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"Cucumber classification" seems almost identical to the letter classification task which is the beginner's tutorial on Tensorflow. I think anyone who knows Pyth

"Cucumber classification" seems almost identical to the letter classification task which is the beginner's tutorial on Tensorflow. I think anyone who knows Python and completed a Coursera or Udacity course could get something implemented.

GFK_of_xmaspast 10y ago
> "Cucumber classification" seems almost identical to the letter classification task Why do you say that?
- sbierwagen 10y ago
  You're looking at the shape of an object, and determining which category it belongs to. It is similar to looking at a handwritten "a" and determining if it belongs to the "a" category.
  - justinsaccount 10y ago
    "Even with this low-res image, the system can only classify a cucumber based on its shape, length and level of distortion. It can't recognize color, texture, scratches and prickles,” Makoto explained. Increasing image resolution by zooming into the cucumber would result in much higher accuracy, but would also increase the training time significantly.
  - GFK_of_xmaspast 10y ago
    That seems incredibly reductionist, and you might as well say they're the same because "you add a bunch of numbers together and see if the result is bigger or less than zero." (Also how do you know or why would you expect that it's categorizing by shape? Neural networks are infamous for finding "irrelevant" features in training data).
    - sbierwagen 10y ago
      I don't understand your objection. Letter recognition takes a bitmap, and sorts it into one of 26 categories, cucumber grading takes a bitmap, and sorts it into one of 9 categories. Of course it's reductionist. Generalizing an abstraction across many things that superficially look different is what programmers do. Reducing problem complexity to make something easier to automate is what programming is for. Saying cucumber grading is like letter recognition is a true generalization that is also useful. Saying that they're both "adding a bunch of numbers" is a true generalization that is less useful. Programming, and (way more) broadly, science and engineering itself, is about finding useful generalizations.
visarga 10y ago
"Cucumber classification"can be solved easily with a C3NN (Cucumber Classification Convolutional Neural Network).

GFK_of_xmaspast 10y ago

> "Cucumber classification" seems almost identical to the letter classification task Why do you say that?

sbierwagen 10y ago
You're looking at the shape of an object, and determining which category it belongs to. It is similar to looking at a handwritten "a" and determining if it belongs to the "a" category.
- justinsaccount 10y ago
  "Even with this low-res image, the system can only classify a cucumber based on its shape, length and level of distortion. It can't recognize color, texture, scratches and prickles,” Makoto explained. Increasing image resolution by zooming into the cucumber would result in much higher accuracy, but would also increase the training time significantly.
- GFK_of_xmaspast 10y ago
  That seems incredibly reductionist, and you might as well say they're the same because "you add a bunch of numbers together and see if the result is bigger or less than zero." (Also how do you know or why would you expect that it's categorizing by shape? Neural networks are infamous for finding "irrelevant" features in training data).
  - sbierwagen 10y ago
    I don't understand your objection. Letter recognition takes a bitmap, and sorts it into one of 26 categories, cucumber grading takes a bitmap, and sorts it into one of 9 categories. Of course it's reductionist. Generalizing an abstraction across many things that superficially look different is what programmers do. Reducing problem complexity to make something easier to automate is what programming is for. Saying cucumber grading is like letter recognition is a true generalization that is also useful. Saying that they're both "adding a bunch of numbers" is a true generalization that is less useful. Programming, and (way more) broadly, science and engineering itself, is about finding useful generalizations.

visarga 10y ago

"Cucumber classification"can be solved easily with a C3NN (Cucumber Classification Convolutional Neural Network).