| // I don't dance now, I make muscle moves... | |
| // Configurable Params | |
| MaxMoveF = 4000 | |
| MaxHoldF = 1.334 * MaxMoveF | |
| MaxTorque = 500 | |
| MaxHoldTorque = 1.334 * MaxTorque | |
| MaxMoveSpeed = 4.5 // m/s | |
| HillParamA = 0.25 // Coefficient of shortening heat in Hill's muscle model | |
| SetAngularDrag(0) |
##VGG16 model for Keras
This is the Keras model of the 16-layer network used by the VGG team in the ILSVRC-2014 competition.
It has been obtained by directly converting the Caffe model provived by the authors.
Details about the network architecture can be found in the following arXiv paper:
Very Deep Convolutional Networks for Large-Scale Image Recognition
K. Simonyan, A. Zisserman
Reverse port tunneling is used to give a user outside of a networks firewall accesst to a computer inside the firewall where direct SSH connections aren't allowed. It works by the in-firewall computer SSH'ing to a middleman computer that then forwards incomming SSH connections on a given port to the firewalled computer.
GatewayPorts yes to /etc/ssh/sshd_config
| """ | |
| Viterbi algorithm for finding the most likely state sequence of a simple | |
| hidden markov model. | |
| # https://en.wikipedia.org/wiki/Viterbi_algorithm | |
| The Model | |
| --------- | |
| The HMMs considered in this code are extremely simple. Every hidden state | |
| is uniquely associated with an output symbol, but the link is "fuzzy". That is, |