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 ...
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...
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 ...
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...
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...