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An empirical study on the effects of different types of noise in image
  classification tasks

An empirical study on the effects of different types of noise in image classification tasks

9 September 2016
G. B. P. D. Costa
Welinton A. Contato
T. S. Nazaré
J. B. Neto
M. Ponti
ArXivPDFHTML

Papers citing "An empirical study on the effects of different types of noise in image classification tasks"

5 / 5 papers shown
Title
One-Shot Item Search with Multimodal Data
One-Shot Item Search with Multimodal Data
Jonghwa Yim
Junghun Kim
D. Shin
21
3
0
27 Nov 2018
Survey of Face Detection on Low-quality Images
Survey of Face Detection on Low-quality Images
Yuqian Zhou
Ding Liu
Thomas Huang
AAML
CVBM
13
59
0
19 Apr 2018
Classification Driven Dynamic Image Enhancement
Classification Driven Dynamic Image Enhancement
Vivek Sharma
Ali Diba
D. Neven
M. S. Brown
Luc Van Gool
Rainer Stiefelhagen
35
66
0
20 Oct 2017
Enhancing the Performance of Convolutional Neural Networks on Quality
  Degraded Datasets
Enhancing the Performance of Convolutional Neural Networks on Quality Degraded Datasets
Jonghwa Yim
Kyung-ah Sohn
13
54
0
18 Oct 2017
Dirty Pixels: Towards End-to-End Image Processing and Perception
Dirty Pixels: Towards End-to-End Image Processing and Perception
Steven Diamond
Vincent Sitzmann
Frank D. Julca-Aguilar
Stephen P. Boyd
Gordon Wetzstein
Felix Heide
24
51
0
23 Jan 2017
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