title: what is output dimension of the inception and vgg16
body: <p>I have used two image net trained models i.e. VGG16 and inception using following lines in python using Keras API; where x is the input image and batch size is for simplicity =1.</p>
  
  <pre><code>VGGbase_model = InceptionV3(weights='imagenet', include_top=False, 
  input_shape=(299,299,3))
  Inceptionbase_model = VGG16(weights='imagenet', include_top=False, 
  input_shape=(224,224,3))
  predictVgg16= VGGbase_model.predict_on_batch(x)
  predictinception= Inceptionbase_model.predict_on_batch(x)
  </code></pre>
  
  <p>I have observed that VGG16 model predict with an output dimension of (1,512) , i understand 512 is the Features as predicted by the VGG16. however the inception model outputs a dimension of 1,8,8,2048.  I understand 2048 is the feature vector as predicted by inception , but what is 8,8 and why VGG16 only have two dimensions while inception have 3. Any comments please. </p>