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Open AccessProceedings Article

Learning to Parse Images

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TLDR
Using parse trees as internal representations of images, credibility networks are able to perform segmentation and recognition simultaneously, removing the need for ad hoc segmentation heuristics.
Abstract
We describe a class of probabilistic models that we call credibility networks. Using parse trees as internal representations of images, credibility networks are able to perform segmentation and recognition simultaneously, removing the need for ad hoc segmentation heuristics. Promising results in the problem of segmenting handwritten digits were obtained.

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Citations
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Dynamic Routing Between Capsules

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Dissertation

Graphical models for visual object recognition and tracking

TL;DR: The approach couples topic models originally developed for text analysis with spatial transformations, and thus consistently accounts for geometric constraints by building integrated scene models, which may discover contextual relationships, and better exploit partially labeled training images.
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Describing Visual Scenes Using Transformed Objects and Parts

TL;DR: This work develops hierarchical, probabilistic models for objects, the parts composing them, and the visual scenes surrounding them and proposes nonparametric models which use Dirichlet processes to automatically learn the number of parts underlying each object category, and objects composing each scene.
References
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Book ChapterDOI

Learning internal representations by error propagation

TL;DR: This chapter contains sections titled: The Problem, The Generalized Delta Rule, Simulation Results, Some Further Generalizations, Conclusion.
Book

Learning internal representations by error propagation

TL;DR: In this paper, the problem of the generalized delta rule is discussed and the Generalized Delta Rule is applied to the simulation results of simulation results in terms of the generalized delta rule.
Journal ArticleDOI

Backpropagation applied to handwritten zip code recognition

TL;DR: This paper demonstrates how constraints from the task domain can be integrated into a backpropagation network through the architecture of the network, successfully applied to the recognition of handwritten zip code digits provided by the U.S. Postal Service.
Book

Vision: A Computational Investigation into the Human Representation and Processing of Visual Information

David Marr
TL;DR: Marr's posthumously published Vision (1982) influenced a generation of brain and cognitive scientists, inspiring many to enter the field of visual perception as discussed by the authors, where the process of vision constructs a set of representations, starting from a description of the input image and culminating with three-dimensional objects in the surrounding environment, a central theme and one that has had farreaching influence in both neuroscience and cognitive science, is the notion of different levels of analysis.