By BVLC/Caffe examples cifar10, it has 3 conv layers with pool/norm and it's accuracy increase to around 82 easily. Now I want to increase my resolution by download the 10 classes of images from imagenet and make the image resolution to 55. Now for the higher resolution and less data 5000 per-class while cifar-10 has 6000 per class. What is the good design strategies this new scenario? Is the performance gonna drop a lot?
Design strategies for higher resolution images for Convolutional neural network?
deep learning;convnet