A Dynamic Inference Model for Object Recognition

What is it about?

The ventral visual stream (VVS) is a fundamental pathway involved in visual object identification and recognition. In this work, we present a hypothesis of a sequence of computations performed by the VVS during object recognition. The operations performed by the inferior temporal (IT) cortex are represented as not being akin to a neural-network, but rather in-line with a dynamic inference instantiation of the untangling notion. The analysis will provide insight in explaining the exceptional proficiency of the VVS.

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Photo by jesse orrico on Unsplash

Photo by jesse orrico on Unsplash

Why is it important?

Presents a framework for an inference-based approach that is biologically inspired via attributes implicated in primate object recognition. The introduced model is an alternative to neural network techniques employing max-pooling, and an alternative to machine learning approaches that consider object categorization rather than classification of object attributes during the recognition process.