stridenumberof pixelsshiftspaddingouterlayerunsupervisedclusteringenvironmentreinforcementcnnneworkarchitectureCconvolutionfeatureextractionlstmsequenceprediction3Dinputimagekernelsize ofconvolutionalfilterbrainbiologicalneuralnetworknodeneuronpoolingsizereducefilteroutputchannelflatten1Dsigmoidactivationfunctionlabelsupervisedfeaturemapconvolutionallayerdeepnetworkmultiplelayersrelunegativevaluessupervisedcnnactivationfunctionneuronactivatedensefullyconnectedunlabeleddropoutnullifysomeneuronstridenumberof pixelsshiftspaddingouterlayerunsupervisedclusteringenvironmentreinforcementcnnneworkarchitectureCconvolutionfeatureextractionlstmsequenceprediction3Dinputimagekernelsize ofconvolutionalfilterbrainbiologicalneuralnetworknodeneuronpoolingsizereducefilteroutputchannelflatten1Dsigmoidactivationfunctionlabelsupervisedfeaturemapconvolutionallayerdeepnetworkmultiplelayersrelunegativevaluessupervisedcnnactivationfunctionneuronactivatedensefullyconnectedunlabeleddropoutnullifysomeneuron

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.


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