flatten1Dsupervisedcnnbrainbiologicalneuralnetworklabelsupervisedunsupervisedclusteringcnnneworkarchitecturestridenumberof pixelsshiftspaddingouterlayerCconvolutionfeatureextractiondensefullyconnectedrelunegativevaluesactivationfunctionneuronactivatelstmsequencepredictionenvironmentreinforcementunlabeled3Dinputimagekernelsize ofconvolutionalfiltersigmoidactivationfunctionnodeneuronfilteroutputchannelpoolingsizereducedeepnetworkmultiplelayersdropoutnullifysomeneuronfeaturemapconvolutionallayerflatten1Dsupervisedcnnbrainbiologicalneuralnetworklabelsupervisedunsupervisedclusteringcnnneworkarchitecturestridenumberof pixelsshiftspaddingouterlayerCconvolutionfeatureextractiondensefullyconnectedrelunegativevaluesactivationfunctionneuronactivatelstmsequencepredictionenvironmentreinforcementunlabeled3Dinputimagekernelsize ofconvolutionalfiltersigmoidactivationfunctionnodeneuronfilteroutputchannelpoolingsizereducedeepnetworkmultiplelayersdropoutnullifysomeneuronfeaturemapconvolutionallayer

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