A Study on the Use of Edge TPUs for Eye Fundus Image Segmentation. (arXiv:2207.12770v1 [eess.IV])

Medical image segmentation can be implemented using Deep Learning methods
with fast and efficient segmentation networks. Single-board computers (SBCs)
are difficult to use to train deep networks due to their memory and processing
limitations. Specific hardware such as Google's Edge TPU makes them suitable
for real time predictions using complex pre-trained networks. In this work, we
study the performance of two SBCs, with and without hardware acceleration for
fundus image segmentation, though the conclusions of this study can be applied …

arxiv edge image segmentation study tpus