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» Learning How to Inpaint from Global Image Statistics
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NIPS
2008
13 years 9 months ago
Natural Image Denoising with Convolutional Networks
We present an approach to low-level vision that combines two main ideas: the use of convolutional networks as an image processing architecture and an unsupervised learning procedu...
Viren Jain, H. Sebastian Seung
MVA
1992
13 years 8 months ago
High Speed Autofocus for Microscopic Images
2 Computational Theory The processing of biological specimens or the 2.1 Overview examination of material surfaces for quality control requires a fast and precise autofocus system....
J. E. Fischer, D. Homeister, J. Lehmler, G. Roos
VISAPP
2008
13 years 9 months ago
Towards the Estimation of Conspicuity with Visual Priors
Traffic signs are designed to be clearly seen by drivers. However a little is known about the visual influence of the traffic sign environment on how it will be perceived. Computer...
Ludovic Simon, Jean-Philippe Tarel, Roland Bremond
MEDIAFORENSICS
2010
13 years 5 months ago
Image dependent log-likelihood ratio allocation for repeat accumulate code-based decoding in data hiding channels
Error correction codes of suitable redundancy are used for ensuring perfect data recovery in noisy channels. For iterative decoding based methods, the decoder needs to be initiali...
Anindya Sarkar, B. S. Manjunath
ICCV
2007
IEEE
14 years 9 months ago
Enabling Users to Guide the Design of Robust Model Fitting Algorithms
Model-based image interpretation extracts high-level information from images using a priori knowledge about the object of interest. The computational challenge in model fitting is...
Matthias Wimmer, Freek Stulp, Bernd Radig