Rather than relying on raw sensory input (or so-called "bottom-up" processes), it seems that V1 is heavily influenced by factors such as prior knowledge about objects in our environment (what's known as "top-down" processing).
So then, this week's topic may be as much about discovery as prior knowledge, so get beavering, dig deep and come up with some Canadian treasure, whether that be inspired by the busy cities, the quiet towns or the huge, beautiful countryside.
Then, the output of one of the models would serve as prior knowledge to the other.
In this paper, we also investigated cluster number K as prior knowledge.
Learner characteristics, such as prior knowledge, working memory capacity, self-efficacy and cognitive load, were taken into account.
These neighbor points' normals are estimated by principal component analysis, and used as prior knowledge to carry out neighborhood clustering.
Most existing fingerprint segmentation methods are statistically based, which require labeled foreground and background blocks as prior knowledge.
Such information can be used as "prior knowledge" under a Bayesian framework and be quantitatively reflected by a prior distribution in Bayesian methods.
While performing a problem-solving process, different kinds of cognitive operations and influences of covariates such as prior knowledge, experience, and motivation come together.
As prior knowledge improves and becomes much more informative, a subjective probability assessment framework (SPAF) is proposed to estimate the prior distribution from prior knowledge.
The key of our approach is utilizing inherent program characteristics as prior knowledge (in addition to microarchitectural configurations) to build a universal predictive model.
