title: Increasing accuracy by changing batch-size and input image size
body: <p>I am extracting a road network from satellite imagery. Herein the pixel classification is binary ( 0 = non-road, 1 = road). Hence, the mask of the complete satellite image which is 6400 x 6400 pixels shows one large road network where each road is connected to another road. For the implementation of the U-net I divided that large image in 625 images of 256 x 256 pixels. </p>
  
  <p>My question is: Can a neural network easier find structure with an increase in batch size (thus can it find structure between different batches), or can it only find structure if the input image size is enlarged?</p>