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ICCV
2011
IEEE
14 years 3 months ago
Adaptive Deconvolutional Networks for Mid and High Level Feature Learning
We present a hierarchical model that learns image decompositions via alternating layers of convolutional sparse coding and max pooling. When trained on natural images, the layers ...
Matthew D. Zeiler, Graham W. Taylor, Rob Fergus
CVPR
2012
IEEE
13 years 5 months ago
Random walks based multi-image segmentation: Quasiconvexity results and GPU-based solutions
We recast the Cosegmentation problem using Random Walker (RW) segmentation as the core segmentation algorithm, rather than the traditional MRF approach adopted in the literature s...
Maxwell D. Collins, Jia Xu, Leo Grady, Vikas Singh

Book
519views
17 years 1 months ago
Information Theory, Inference, and Learning Algorithms
This book is aimed at senior undergraduates and graduate students in Engineering, Science, Mathematics, and Computing. It expects familiarity with calculus, probability theory, and...
David J. C. MacKay
ICIP
2005
IEEE
16 years 4 months ago
Flow lookup and biological motion perception
Optical flow in monocular video can serve as a key for recognizing and tracking the three-dimensional pose of human subjects. In comparison with prior work using silhouettes as a ...
Nicholas R. Howe
ICIP
2009
IEEE
16 years 4 months ago
Dequantizing Compressed Sensing With Non-gaussian Constraints
In this paper, following the Compressed Sensing (CS) paradigm, we study the problem of recovering sparse or compressible signals from uniformly quantized measurements. We present ...