*Application of Deep Learning Methods for Detection and Tracking of Players DOI: http://dx.doi.org/10.5772/intechopen.96308*

more accurately than conventional RNNs. In the recurrent hidden layers, the LSTM contains special units called memory blocks. Those units contain memory cells, that have self-connections storing the temporal state of the network, and gates, which are special multiplicative units that control the flow of information. The flow of input activations into the memory cell is being controlled by the input gate, while the output gate controls the output flow of cell activations into the rest of the network. The forget gate scales the internal state of the cell before adding it as input to the cell through the self-recurrent connection of the cell, thus causing the adaptive forgetting or resetting the cell's memory.
