>What are techniques or best practices for detecting/segmenting large objects in high resolution images? Some problems I run into are training with large image chip sizes

The first thing that came to my mind was gradient accumulation if you have limited GPU memory. Fitting an image of that size on a single GPU could result in a very small batch, which is not so good for training speed and stability.

PyTorch lightning offers such a feature if you're using PyTorch.