Name
Abstract | ||
|---|---|---|
For all the ways convolutional neural nets have revolutionized computer vision in recent years, one important aspect has received surprisingly little attention: the effect of image size on the accuracy of tasks being trained for. Typically, to be efficient, the input images are resized to a relatively small spatial resolution (e.g. 224 × 224), and both training and inference are carried out at thi... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ICCV48922.2021.00055 | 2021 IEEE/CVF International Conference on Computer Vision (ICCV) |
Keywords | DocType | ISBN |
Training,Measurement,Adaptation models,Computer vision,Visualization,Computational modeling,Machine vision | Conference | 978-1-6654-2812-5 |
Citations | PageRank | References |
3 | 0.43 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| hossein talebi | 1 | 48 | 3.75 |
| Peyman Milanfar | 2 | 3 | 0.77 |