Learning to combine foveal glimpses with a third-order Boltzmann machine
| 
68 | 
45 | 
0
Abstract
We describe a model based on a Boltzmann machine with third-order connections that can learn how to accumulate information about a shape over several fixations. The model uses a retina that only has enough high resolution pixels to cover a small area of the image, so it must decide on a sequence of fixations and it must combine the “glimpse” at each fixation with the location of the fixation before integrating the information with information from other glimpses of the same object. We evaluate this model on a synthetic dataset and two image classification datasets, showing that it can perform at least as well as a model trained on whole images.
还没有评论，说两句吧！
热门资源
The Variational S...
Unlike traditional images which do not offer in...
Learning to Predi...
Much of model-based reinforcement learning invo...
Stratified Strate...
In this paper we introduce Stratified Strategy ...
Learning to learn...
The move from hand-designed features to learned...
A Mathematical Mo...
Direct democracy, where each voter casts one vo...
智能在线
400-630-6780
聆听.建议反馈
E-mail: support@tusaishared.com
资源分类
