nodeneuronpoolingsizereducelabelsuperviseddensefullyconnectedunlabeleddropoutnullifysomeneuronfilteroutputchannelenvironmentreinforcementfeaturemapconvolutionallayercnnneworkarchitecturekernelsize ofconvolutionalfilterpaddingouterlayerstridenumberof pixelsshiftsunsupervisedclusteringdeepnetworkmultiplelayerslstmsequencepredictionsupervisedregressionsigmoidactivationfunctionflatten1DCconvolutionfeatureextraction3Dinputimagerelunegativevaluesactivationfunctionneuronactivatesupervisedcnnnodeneuronpoolingsizereducelabelsuperviseddensefullyconnectedunlabeleddropoutnullifysomeneuronfilteroutputchannelenvironmentreinforcementfeaturemapconvolutionallayercnnneworkarchitecturekernelsize ofconvolutionalfilterpaddingouterlayerstridenumberof pixelsshiftsunsupervisedclusteringdeepnetworkmultiplelayerslstmsequencepredictionsupervisedregressionsigmoidactivationfunctionflatten1DCconvolutionfeatureextraction3Dinputimagerelunegativevaluesactivationfunctionneuronactivatesupervisedcnn

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