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4 results found.

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Going deeper with convolutions
Article
Article
Christian Szegedy; Wei Liu; Yangqing Jia; Pierre Sermanet; Scott Reed; Dragomir Anguelov; Dumitru Erhan; Vincent Vanhoucke · OpenAlex · 2015
We propose a deep convolutional neural network architecture codenamed Inception that achieves the new state of the art for classification and detection in the ImageNet Large-Scale Visual Recognition Challenge 2014 (ILSVR...
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ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
Text / resource
Text / resource
Xiangyu Zhang; Xinyu Zhou; Mengxiao Lin; Jian Sun · OpenAlex · 2018
We introduce an extremely computation-efficient CNN architecture named ShuffleNet, which is designed specially for mobile devices with very limited computing power (e.g., 10-150 MFLOPs). The new architecture utilizes two...
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Caffe
Article
Article
Yangqing Jia; Evan Shelhamer; Jeff Donahue; Sergey Karayev; Jonathan Long; Ross Girshick; Sergio Guadarrama; Trevor Darrell · OpenAlex · 2014
Caffe provides multimedia scientists and practitioners with a clean and modifiable framework for state-of-the-art deep learning algorithms and a collection of reference models. The framework is a BSD-licensed C++ library...
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Path Aggregation Network for Instance Segmentation
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Text / resource
Shu Liu; Lu Qi; Haifang Qin; Jianping Shi; Jiaya Jia · OpenAlex · 2018
The way that information propagates in neural networks is of great importance. In this paper, we propose Path Aggregation Network (PANet) aiming at boosting information flow in proposal-based instance segmentation framew...
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