Sciweavers

5 search results - page 1 / 1
» Adaptive Deconvolutional Networks for Mid and High Level Fea...
Sort
View
ICCV
2011
IEEE
12 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
PR
2007
151views more  PR 2007»
13 years 3 months ago
Learning to display high dynamic range images
In this paper, we present a learning-based image processing technique. We have developed a novel method to map high dynamic range scenes to low dynamic range images for display in...
Guoping Qiu, Jiang Duan, Graham D. Finlayson
BMCBI
2010
224views more  BMCBI 2010»
13 years 3 months ago
An adaptive optimal ensemble classifier via bagging and rank aggregation with applications to high dimensional data
Background: Generally speaking, different classifiers tend to work well for certain types of data and conversely, it is usually not known a priori which algorithm will be optimal ...
Susmita Datta, Vasyl Pihur, Somnath Datta
ICIP
1999
IEEE
14 years 5 months ago
A Neural Network Approach to Interactive Content-Based Retrieval of Video Databases
A neural network scheme is presented in this paper for adaptive video indexing and retrieval. First, a limited but characteristic amount of frames are extracted from each video sc...
Nikolaos D. Doulamis, Anastasios D. Doulamis, Stef...
ATMOS
2007
177views Optimization» more  ATMOS 2007»
13 years 5 months ago
Approximate dynamic programming for rail operations
Abstract. Approximate dynamic programming offers a new modeling and algorithmic strategy for complex problems such as rail operations. Problems in rail operations are often modeled...
Warren B. Powell, Belgacem Bouzaïene-Ayari