2010
NeurIPS
NeurIPS 2010
Learning to combine foveal glimpses with a third-order Boltzmann machine
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."
🌱
Topic Pioneer
- Attention
🌉
Interdisciplinary Bridge
- Artificial Intelligence and Computer Vision
📈
Trend Setter
- Multimodal Learning
🐣
Hot Topic Early Bird
- generative model
Authors
Topics
Artificial Intelligence > Core AI > Multimodal Learning
Machine Learning > Learning Types > Self-Supervised Learning
Deep Learning > Architectures > Neural Networks
Deep Learning > Models > Generative Models
Computer Vision > Analysis > Object Detection
Computer Vision > Analysis > Scene Understanding
Computer Vision > Core AI > Multimodal Learning
Computer Vision > Core AI > Computer Vision
Deep Learning > Techniques > Attention
Computer Vision > Analysis > Image Classification