unsupervisedclusteringlabelsupervisednodeneuronfilteroutputchannelpaddingouterlayerlstmsequencepredictionunlabeledstridenumberof pixelsshiftskernelsize ofconvolutionalfilterdeepnetworkmultiplelayerscnnneworkarchitecturebrainbiologicalneuralnetwork3Dinputimagesupervisedcnnflatten1DfeaturemapconvolutionallayerdropoutnullifysomeneuronactivationfunctionneuronactivateenvironmentreinforcementpoolingsizereducedensefullyconnectedCconvolutionfeatureextractionrelunegativevaluessigmoidactivationfunctionunsupervisedclusteringlabelsupervisednodeneuronfilteroutputchannelpaddingouterlayerlstmsequencepredictionunlabeledstridenumberof pixelsshiftskernelsize ofconvolutionalfilterdeepnetworkmultiplelayerscnnneworkarchitecturebrainbiologicalneuralnetwork3Dinputimagesupervisedcnnflatten1DfeaturemapconvolutionallayerdropoutnullifysomeneuronactivationfunctionneuronactivateenvironmentreinforcementpoolingsizereducedensefullyconnectedCconvolutionfeatureextractionrelunegativevaluessigmoidactivationfunction

CNN - Call List

(Print) Use this randomly generated list as your call list when playing the game. Place some kind of mark (like an X, a checkmark, a dot, tally mark, etc) on each cell as you announce it, to keep track. You can also cut out each item, place them in a bag and pull words from the bag.


1
G G
2
B B
3
O O
4
G G
5
N N
6
O O
7
I
8
B B
9
N N
10
N N
11
I I
12
O O
13
B B
14
G G
15
O O
16
O O
17
I I
18
G G
19
N N
20
I I
21
I I
22
B B
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G G
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B B
  1. G-clustering
    G-unsupervised
  2. B-supervised
    B-label
  3. O-neuron
    O-node
  4. G-output channel
    G-filter
  5. N-outer layer
    N-padding
  6. O-sequence prediction
    O-lstm
  7. I-unlabeled
  8. B-number of pixels shifts
    B-stride
  9. N-size of convolutional filter
    N-kernel
  10. N-multiple layers
    N-deep network
  11. I-nework architecture
    I-cnn
  12. O-biological neural network
    O-brain
  13. B-input image
    B-3D
  14. G-cnn
    G-supervised
  15. O-1D
    O-flatten
  16. O-convolutional layer
    O-feature map
  17. I-nullify some neuron
    I-dropout
  18. G-neuron activate
    G-activation function
  19. N-reinforcement
    N-environment
  20. I-size reduce
    I-pooling
  21. I-fully connected
    I-dense
  22. B-feature extraction
    B-Cconvolution
  23. G-negative values
    G-relu
  24. B-activation function
    B-sigmoid