@inproceedings{ac4d84bcaa03460b94939d72d7469721,
title = "A Dynamic Convolutional Layer for short rangeweather prediction",
abstract = "We present a new deep network layer called 'Dynamic Convolutional Layer' which is a generalization of the convolutional layer. The conventional convolutional layer uses filters that are learned during training and are held constant during testing. In contrast, the dynamic convolutional layer uses filters that will vary from input to input during testing. This is achieved by learning a function that maps the input to the filters. We apply the dynamic convolutional layer to the application of short range weather prediction and show performance improvements compared to other baselines.",
author = "Benjamin Klein and Lior Wolf and Yehuda Afek",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015 ; Conference date: 07-06-2015 Through 12-06-2015",
year = "2015",
month = oct,
day = "14",
doi = "10.1109/CVPR.2015.7299117",
language = "الإنجليزيّة",
series = "Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition",
publisher = "IEEE Computer Society",
pages = "4840--4848",
booktitle = "IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015",
address = "الولايات المتّحدة",
}