labelsupervisedkernelsize ofconvolutionalfilter3DinputimagefilteroutputchanneldeepnetworkmultiplelayerssupervisedcnndropoutnullifysomeneuronenvironmentreinforcementCconvolutionfeatureextractionstridenumberof pixelsshiftsfeaturemapconvolutionallayersigmoidactivationfunctionunlabeledunsupervisedclusteringflatten1Dactivationfunctionneuronactivatecnnneworkarchitecturepoolingsizereducedensefullyconnectedpaddingouterlayernodeneuronlstmsequencepredictionsupervisedregressionrelunegativevalueslabelsupervisedkernelsize ofconvolutionalfilter3DinputimagefilteroutputchanneldeepnetworkmultiplelayerssupervisedcnndropoutnullifysomeneuronenvironmentreinforcementCconvolutionfeatureextractionstridenumberof pixelsshiftsfeaturemapconvolutionallayersigmoidactivationfunctionunlabeledunsupervisedclusteringflatten1Dactivationfunctionneuronactivatecnnneworkarchitecturepoolingsizereducedensefullyconnectedpaddingouterlayernodeneuronlstmsequencepredictionsupervisedregressionrelunegativevalues

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