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An Empirical Method to Quantify the Peripheral Performance Degradation in Deep Networks

An Empirical Method to Quantify the Peripheral Performance Degradation in Deep Networks

C. Wloka
John K. Tsotsos
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Papers citing "An Empirical Method to Quantify the Peripheral Performance Degradation in Deep Networks"

5 / 5 papers shown
Title
On Translation Invariance in CNNs: Convolutional Layers can Exploit Absolute Spatial Location
On Translation Invariance in CNNs: Convolutional Layers can Exploit Absolute Spatial Location
O. Kayhan
Jan van Gemert
275
234
0
16 Mar 2020
How Much Position Information Do Convolutional Neural Networks Encode?
How Much Position Information Do Convolutional Neural Networks Encode?
Md. Amirul Islam
Sen Jia
Neil D. B. Bruce
SSL
230
346
0
22 Jan 2020
Efficient ConvNet-based Object Detection for Unmanned Aerial Vehicles by Selective Tile Processing
Efficient ConvNet-based Object Detection for Unmanned Aerial Vehicles by Selective Tile Processing
George Plastiras
C. Kyrkou
T. Theocharides
17
55
0
14 Nov 2019
Making Convolutional Networks Shift-Invariant Again
Making Convolutional Networks Shift-Invariant Again
Richard Y. Zhang
OOD
56
794
0
25 Apr 2019
Synscapes: A Photorealistic Synthetic Dataset for Street Scene Parsing
Synscapes: A Photorealistic Synthetic Dataset for Street Scene Parsing
Magnus Wrenninge
Jonas Unger
36
185
0
19 Oct 2018

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