CenterNet
Posted by SNC_official
Copy the project to Neural Network Console Cloud
Network Architecture : Main
Type | Value |
---|---|
Output | 3,006,793 |
CostParameter | 15,379,272 |
CostAdd | 1,126,720 |
CostMultiply | 945,696 |
CostMultiplyAdd | 1,597,149,184 |
CostDivision | 3,140 |
CostExp | 29,792 |
CostIf | 1,306,768 |
Network Architecture : Runtime
Type | Value |
---|---|
Output | 2,900,160 |
CostParameter | 15,379,272 |
CostAdd | 1,095,360 |
CostMultiply | 893,952 |
CostMultiplyAdd | 1,597,149,184 |
CostDivision | 3,136 |
CostExp | 3,136 |
CostIf | 1,299,712 |
Training Procedure : Optimizer
Optimize network “Main” using “Training” dataset.
- Batch size : 256
- Solver : Adam
- Learning rate(Alpha) : 0.001
- decayed every 1 iteration using an exponential rate of 0.5 .
- Beta1 : 0.9
- Beta2 : 0.999
- Epsilon : 1e-08
- Weight decay : 0.001
Experimental Result : Learning Curve
References
- Sony Corporation. Neural Network Console : Not just train and evaluate. You can design neural networks with fast and intuitive GUI. https://dl.sony.com/
- Sony Corporation. Neural Network Libraries : An open source software to make research, development and implementation of neural network more efficient. https://nnabla.org/
- Convolution – Chen et al., DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs. https://arxiv.org/abs/1606.00915, Yu et al., Multi-Scale Context Aggregation by Dilated Convolutions. https://arxiv.org/abs/1511.07122
- BatchNormalization – Ioffe and Szegedy, Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift. https://arxiv.org/abs/1502.03167
- ReLU – Vinod Nair, Geoffrey E. Hinton. Rectified Linear Units Improve Restricted Boltzmann Machines. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.165.6419&rep=rep1&type=pdf
- Adam – Kingma and Ba, Adam: A Method for Stochastic Optimization. https://arxiv.org/abs/1412.6980