Application.CV.IMAGE_CLASSIFICATION models in the BasicModelZoo.See: Description
| Class | Description |
|---|---|
| AlexNet |
AlexNet contains a generic implementation of AlexNet adapted from [torchvision
implmentation](https://github.com/pytorch/vision/blob/master/torchvision/models/alexnet.py) |
| AlexNet.Builder |
The Builder to construct a
AlexNet object. |
| GoogLeNet |
GoogLeNet uses a stack of a total of 9 inception blocks and global average pooling to generate
its estimates.
|
| GoogLeNet.Builder |
The Builder to construct a
GoogLeNet object. |
| LeNet |
The model was introduced (and named for) Yann Lecun, for the purpose of recognizing handwritten
digits in images [LeNet5](http://yann.lecun.com/exdb/lenet/).
|
| LeNet.Builder |
The Builder to construct a
LeNet object. |
| MlpModelLoader |
Model loader for MLP models.
|
| NiN |
NiN uses convolutional layers with window shapes of 11×11 , 5×5 , and 3×3 , and the corresponding
numbers of output channels are the same as in AlexNet.
|
| NiN.Builder |
The Builder to construct a
NiN object. |
| ResNetModelLoader |
Model loader for ResNet_V1.
|
| ResNetV1 |
ResNetV1 contains a generic implementation of ResNet adapted from
https://github.com/tornadomeet/ResNet/blob/master/symbol_resnet.py (Original author Wei Wu) by
Antti-Pekka Hynninen. |
| ResNetV1.Builder |
The Builder to construct a
ResNetV1 object. |
| SqueezeNet |
SqueezeNet contains a generic implementation of Squeezenet adapted from [torchvision
implmentation](https://github.com/pytorch/vision/blob/master/torchvision/models/squeezenet.py) |
| VGG |
VGG model from the "Very Deep Convolutional Networks for Large-Scale Image Recognition"
https://arxiv.org/abs/1409.1556 paper.
|
| VGG.Builder |
The Builder to construct a
VGG object. |
Application.CV.IMAGE_CLASSIFICATION models in the BasicModelZoo.