Spatially-sparse convolutional neural networks. Graham, B. arXiv:1409.6070 [cs], September, 2014. arXiv: 1409.6070Paper abstract bibtex Convolutional neural networks (CNNs) perform well on problems such as handwriting recognition and image classification. However, the performance of the networks is often limited by budget and time constraints, particularly when trying to train deep networks.
@article{graham_spatially-sparse_2014,
title = {Spatially-sparse convolutional neural networks},
url = {http://arxiv.org/abs/1409.6070},
abstract = {Convolutional neural networks (CNNs) perform well on problems such as handwriting recognition and image classification. However, the performance of the networks is often limited by budget and time constraints, particularly when trying to train deep networks.},
language = {en},
urldate = {2019-06-14},
journal = {arXiv:1409.6070 [cs]},
author = {Graham, Benjamin},
month = sep,
year = {2014},
note = {arXiv: 1409.6070},
keywords = {Computer Science - Computer Vision and Pattern Recognition, Computer Science - Neural and Evolutionary Computing}
}
Downloads: 0
{"_id":"HL5tCX3C8kSBNa79X","bibbaseid":"graham-spatiallysparseconvolutionalneuralnetworks-2014","authorIDs":[],"author_short":["Graham, B."],"bibdata":{"bibtype":"article","type":"article","title":"Spatially-sparse convolutional neural networks","url":"http://arxiv.org/abs/1409.6070","abstract":"Convolutional neural networks (CNNs) perform well on problems such as handwriting recognition and image classification. However, the performance of the networks is often limited by budget and time constraints, particularly when trying to train deep networks.","language":"en","urldate":"2019-06-14","journal":"arXiv:1409.6070 [cs]","author":[{"propositions":[],"lastnames":["Graham"],"firstnames":["Benjamin"],"suffixes":[]}],"month":"September","year":"2014","note":"arXiv: 1409.6070","keywords":"Computer Science - Computer Vision and Pattern Recognition, Computer Science - Neural and Evolutionary Computing","bibtex":"@article{graham_spatially-sparse_2014,\n\ttitle = {Spatially-sparse convolutional neural networks},\n\turl = {http://arxiv.org/abs/1409.6070},\n\tabstract = {Convolutional neural networks (CNNs) perform well on problems such as handwriting recognition and image classification. However, the performance of the networks is often limited by budget and time constraints, particularly when trying to train deep networks.},\n\tlanguage = {en},\n\turldate = {2019-06-14},\n\tjournal = {arXiv:1409.6070 [cs]},\n\tauthor = {Graham, Benjamin},\n\tmonth = sep,\n\tyear = {2014},\n\tnote = {arXiv: 1409.6070},\n\tkeywords = {Computer Science - Computer Vision and Pattern Recognition, Computer Science - Neural and Evolutionary Computing}\n}\n\n","author_short":["Graham, B."],"key":"graham_spatially-sparse_2014","id":"graham_spatially-sparse_2014","bibbaseid":"graham-spatiallysparseconvolutionalneuralnetworks-2014","role":"author","urls":{"Paper":"http://arxiv.org/abs/1409.6070"},"keyword":["Computer Science - Computer Vision and Pattern Recognition","Computer Science - Neural and Evolutionary Computing"],"downloads":0,"html":""},"bibtype":"article","biburl":"https://bibbase.org/zotero/asneha213","creationDate":"2019-07-08T00:48:54.944Z","downloads":0,"keywords":["computer science - computer vision and pattern recognition","computer science - neural and evolutionary computing"],"search_terms":["spatially","sparse","convolutional","neural","networks","graham"],"title":"Spatially-sparse convolutional neural networks","year":2014,"dataSources":["fjacg9txEnNSDwee6"]}