I was trying to create a dataset for animal detection using convolution neural network. It was for some open source project. For the training and testing, I thought to create a dataset myself. for example , a dataset of 500 cats, 500 dogs, and 500 cows as an initial dataset. While creating a dataset , I got the confusion about the position of animals in the image. In the digit recognition, it is said that the digit should be centered.My doubt is whether that is necessary??whether the neural network could be trained by images in which objects are not centered. Or is there any conventions in creating a dataset for neural network??
Above given an image of MNIST digit identification where the digits are centered.
I just want to know whether could I add images like the below (object is not centered and also occluded) to my cow detection dataset?? Or is there any mechanism to create good dataset for an image recognition problem using neural networks??