Work on smaller input size

[chiuhc]

Hi,
I was trying to work on resized input images close to 256X256 rather than 50% of Raw camera image size (1020X680). Turns out the confidence matrix become quite small and hits the performance.

I was thinking about modifying squeeze_net structure. Your squeeze_net has 1 extra 2X2 max_pooling than squeeze_net v1.1. Did you retrain the squeeze_net model you provided on imagenet data?
I wonder if I can remove it such that the final confidence matrix resolution is larger?
Do I have to retrain squeezenet backbone on image_net data if I do so?
Any other suggestion? would you recommend doing upconvolution in FC1?

Many thanks,