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» Extracting Propositions from Trained Neural Networks
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IJCNN
2007
IEEE
15 years 6 months ago
Random Feature Subset Selection for Analysis of Data with Missing Features
Abstract - We discuss an ensemble-of-classifiers based algorithm for the missing feature problem. The proposed approach is inspired in part by the random subspace method, and in pa...
Joseph DePasquale, Robi Polikar
IROS
2008
IEEE
138views Robotics» more  IROS 2008»
15 years 6 months ago
Deep belief net learning in a long-range vision system for autonomous off-road driving
Abstract— We present a learning-based approach for longrange vision that is able to accurately classify complex terrain at distances up to the horizon, thus allowing high-level s...
Raia Hadsell, Ayse Erkan, Pierre Sermanet, Marco S...
ICDAR
2009
IEEE
14 years 9 months ago
Recognition of Handwritten Numerical Fields in a Large Single-Writer Historical Collection
This paper presents a segmentation-based handwriting recognizer and the performance that it achieves on the numerical fields extracted from a large single-writer historical collec...
Marius Bulacu, Axel Brink, Tijn van der Zant, Lamb...
ICCV
2011
IEEE
13 years 11 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
GECCO
2006
Springer
147views Optimization» more  GECCO 2006»
15 years 3 months ago
Evolving a real-world vehicle warning system
Many serious automobile accidents could be avoided if drivers were warned of impending crashes before they occur. Creating such warning systems by hand, however, is a difficult an...
Nate Kohl, Kenneth O. Stanley, Risto Miikkulainen,...