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Status: Unchecked ×Keyword: image scaling ×Clear all

2 claims from 1 paper

1. Computer Science › Advanced Neural Network Applications

   Dynamic Resolution Network

   Zhu, Han, Wu et al. · arXiv (Cornell University) · 2021

   The paper proposes a network that picks an input resolution for each image, aiming to cut computation while keeping or improving recognition accuracy, and tests it on benchmark networks and datasets.

   Unchecked2 claims
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   1. UncheckedThe authors observe that, with the same neural network, the smallest image resolution that still gives an accurate prediction differs from one image to another.“In this paper, we observe that the smallest resolution for accurately predicting the given image is different using the same neural network.”
   2. UncheckedA dynamic-resolution ResNet-50 matched the original's accuracy with about 34% less computation, or gained 1.4% accuracy with 10% less, on ImageNet.“For instance, DR-ResNet-50 achieves similar performance with an about 34% computation reduction, while gaining 1.4% accuracy increase with 10% computation reduction compared to the original ResNet-50 on ImageNet.”