杨培文 (Yang Peiwen) ypwhs

## residual_network.py
"""
Clean and simple Keras implementation of network architectures described in:
    - (ResNet-50) [Deep Residual Learning for Image Recognition](https://arxiv.org/pdf/1512.03385.pdf).
    - (ResNeXt-50 32x4d) [Aggregated Residual Transformations for Deep Neural Networks](https://arxiv.org/pdf/1611.05431.pdf).

Python 3.
"""

from keras import layers
from keras import models

## fire_detect.ipynb

      
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                ypwhs
                / fire_detect.ipynb
            
            
              Created
              December 30, 2016 08:28
                — forked from mlhy/fire_detect.ipynb
            
              
                fire detect
              
          
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## neural.c
/*
  The "hello world" of neural networks: a simple 3-layer feed-forward
  network that implements an XOR logic gate.

  The first layer is the input layer. It has two neurons a and b, which
  are the two inputs to the XOR gate.

  The middle layer is the hidden layer. This has two neurons h1, h2 that
  will learn what it means to be an XOR gate.
	"""
	Clean and simple Keras implementation of network architectures described in:
	- (ResNet-50) [Deep Residual Learning for Image Recognition](https://arxiv.org/pdf/1512.03385.pdf).
	- (ResNeXt-50 32x4d) [Aggregated Residual Transformations for Deep Neural Networks](https://arxiv.org/pdf/1611.05431.pdf).

	Python 3.
	"""

	from keras import layers
	from keras import models
	/*
	The "hello world" of neural networks: a simple 3-layer feed-forward
	network that implements an XOR logic gate.

	The first layer is the input layer. It has two neurons a and b, which
	are the two inputs to the XOR gate.

	The middle layer is the hidden layer. This has two neurons h1, h2 that
	will learn what it means to be an XOR gate.