About: SqueezeNet

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SqueezeNet is the name of a deep neural network for computer vision that was released in 2016. SqueezeNet was developed by researchers at DeepScale, University of California, Berkeley, and Stanford University. In designing SqueezeNet, the authors' goal was to create a smaller neural network with fewer parameters that can more easily fit into computer memory and can more easily be transmitted over a computer network.

Attributes	Values
rdf:type	Thing software schema:CreativeWork work wikidata:Q386724 Software
rdfs:label	SqueezeNet (en)
rdfs:comment	SqueezeNet is the name of a deep neural network for computer vision that was released in 2016. SqueezeNet was developed by researchers at DeepScale, University of California, Berkeley, and Stanford University. In designing SqueezeNet, the authors' goal was to create a smaller neural network with fewer parameters that can more easily fit into computer memory and can more easily be transmitted over a computer network. (en)
foaf:name	SqueezeNet (en)
name	SqueezeNet (en)
dcterms:subject	Deep learning software applications Software using the BSD license Object recognition and categorization Artificial neural networks
Wikipage page ID	57410739 (xsd:integer)
Wikipage revision ID	1109253828 (xsd:integer)
Link from a Wikipage to another Wikipage	Caffe (software) BSD license PyTorch Onnx DeepScale Deep neural network Bear Transit Deep learning software applications Software using the BSD license Apache MXNet Apple Inc. Lidar MATLAB Smartphone Stanford University Computer vision Baidu Object recognition and categorization FPGA TensorFlow Object detection Artificial neural networks AlexNet Keras Bill Dally Synopsys Imagination Technologies Kurt Keutzer Neural Style Transfer Wolfram Mathematica Xilinx ImageNet Forrest Iandola
Link from a Wikipage to an external page	https://github.com/DeepScale/SqueezeNet
sameAs	SqueezeNet SqueezeNet
dbp:wikiPageUsesTemplate	dbt:COI dbt:Infobox_software dbt:Start_date_and_age dbt:When dbt:Yes dbt:Maybe
author	Forrest Iandola, Song Han, Matthew W. Moskewicz, Khalid Ashraf, Bill Dally, Kurt Keutzer (en)
genre	Deep neural network
latest release version	0001-02-01 (xsd:gMonthDay)
license	BSD license
released	2016-02-22 (xsd:date)
repo	https://github.com/DeepScale/SqueezeNet
has abstract	SqueezeNet is the name of a deep neural network for computer vision that was released in 2016. SqueezeNet was developed by researchers at DeepScale, University of California, Berkeley, and Stanford University. In designing SqueezeNet, the authors' goal was to create a smaller neural network with fewer parameters that can more easily fit into computer memory and can more easily be transmitted over a computer network. (en)
prov:wasDerivedFrom	wikipedia-en:SqueezeNet?oldid=1109253828&ns=0
page length (characters) of wiki page	14630 (xsd:nonNegativeInteger)
latest release version	v1.1
release date	2016-02-22 (xsd:date)
author	Bill Dally Kurt Keutzer Forrest Iandola
genre	Deep neural network
license	BSD license
foaf:isPrimaryTopicOf	wikipedia-en:SqueezeNet
is Link from a Wikipage to another Wikipage of	DeepScale Forrest N. Iandola Kurt Keutzer
is foaf:primaryTopic of	wikipedia-en:SqueezeNet

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