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» Extracting Propositions from Trained Neural Networks
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BMCBI
2007
141views more  BMCBI 2007»
14 years 9 months ago
Artificial neural network models for prediction of intestinal permeability of oligopeptides
Background: Oral delivery is a highly desirable property for candidate drugs under development. Computational modeling could provide a quick and inexpensive way to assess the inte...
Eunkyoung Jung, Junhyoung Kim, Minkyoung Kim, Dong...
ICPR
2006
IEEE
15 years 10 months ago
Rotation-Invariant Neoperceptron
Approaches based on local features and descriptors are increasingly used for the task of object recognition due to their robustness with regard to occlusions and geometrical defor...
Beat Fasel, Daniel Gatica-Perez
FLAIRS
2008
15 years 1 days ago
The Introspective Robot: Using Self-Prediction to Improve Robot Learning
We investigate the use of self-predicting neural networks for autonomous robot learning within noisy or partially predictable environments. A benchmark experiment is performed in ...
James B. Marshall, Neil K. Makhija, Zachary D. Rot...
ICML
2010
IEEE
14 years 10 months ago
3D Convolutional Neural Networks for Human Action Recognition
We consider the fully automated recognition of actions in uncontrolled environment. Most existing work relies on domain knowledge to construct complex handcrafted features from in...
Shuiwang Ji, Wei Xu, Ming Yang, Kai Yu
PR
2007
165views more  PR 2007»
14 years 9 months ago
A trainable feature extractor for handwritten digit recognition
This article focusses on the problems of feature extraction and the recognition of handwritten digits. A trainable feature extractor based on the LeNet5 convolutional neural netwo...
Fabien Lauer, Ching Y. Suen, Gérard Bloch