Which neural networks are suitable for visual place recognition? I am doing a project on visual place recognition in changing environments.  The CNN used here is mostly AlexNet, and a feature vector is constructed from layer 3.
Does anyone know of similar work using other CNNs, for example, VGGnet (which I am trying to use) and the corresponding layers?
I have been trying out the different layers of VGGnet-16.  I am trying to get the nearest correspondence to the query image by using the cosine difference between the query image and database images. So far no good results.
Neural networks construct increasingly complex representations of data on each of their layers , so you are free to choose any neural network architechture for this purpose . since the lower layers of neural network (layers near the input layer) mostly compute low level representations of the image (like gabor filters etc) most architechtures won't have much difference at this level. so you can use VGGnet if you want with proper fine-tuning from layer 3 itself.