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Image classification using Deep Neural Networks that preserve the privacy of both the input image and the model being used, has received considerable attention in the last couple of years. Recent work in this area have shown that it is possible to perform image classification with realistically sized networks using e.g., Garbled Circuits as in XONN (USENIX '19) or MPC (CrypTFlow, Eprint '19). These, and other prior work, require models to be either trained in a specific way or postprocessed inarXiv:1910.12435v1 fatcat:i5jxhze7zvgqjmel4rq4i6dljm