flatten 1D supervised cnn brain biological neural network label supervised unsupervised clustering cnn nework architecture stride number of pixels shifts padding outer layer Cconvolution feature extraction dense fully connected relu negative values activation function neuron activate lstm sequence prediction environment reinforcement unlabeled 3D input image kernel size of convolutional filter sigmoid activation function node neuron filter output channel pooling size reduce deep network multiple layers dropout nullify some neuron feature map convolutional layer flatten 1D supervised cnn brain biological neural network label supervised unsupervised clustering cnn nework architecture stride number of pixels shifts padding outer layer Cconvolution feature extraction dense fully connected relu negative values activation function neuron activate lstm sequence prediction environment reinforcement unlabeled 3D input image kernel size of convolutional filter sigmoid activation function node neuron filter output channel pooling size reduce deep network multiple layers dropout nullify some neuron feature map convolutional layer
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.
O-1D
O-flatten
G-cnn
G-supervised
O-biological neural network
O-brain
B-supervised
B-label
G-clustering
G-unsupervised
I-nework architecture
I-cnn
B-number of pixels shifts
B-stride
N-outer layer
N-padding
B-feature extraction
B-Cconvolution
I-fully connected
I-dense
G-negative values
G-relu
G-neuron activate
G-activation function
O-sequence prediction
O-lstm
N-reinforcement
N-environment
I-unlabeled
B-input image
B-3D
N-size of convolutional filter
N-kernel
B-activation function
B-sigmoid
O-neuron
O-node
G-output channel
G-filter
I-size reduce
I-pooling
N-multiple layers
N-deep network
I-nullify some neuron
I-dropout
O-convolutional layer
O-feature map