Table of Contents
What is sparse in image processing?
Sparse representation theory puts forward an emerging, highly effective, and universal such model. Its core idea is the description of the data as a linear combination of few building blocks – atoms – taken from a pre-defined dictionary of such fundamental elements.
Why is sparse represented?
Sparse representation attracts great attention as it can significantly save computing resources and find the characteristics of data in a low-dimensional space. Thus, it can be widely applied in engineering fields such as dictionary learning, signal reconstruction, image clustering, feature selection, and extraction.
What is sparse domain?
Here we declare our sparse domain. The sparse keyword indicates that it will be used to only represent a subset of its bounding domain’s indices, and that arrays declared using it will store a zero value (described further below) for all indices in the set dnsDom – spsDom .
What is deep learning in NLP?
NLP stands for natural language processing and refers to the ability of computers to process text and analyze human language. Deep learning refers to the use of multilayer neural networks in machine learning.
What is labeled line coding?
An alternative coding mechanism is the “labeled-line code” (also termed “place code”). Here, the magnitude of a stimulus is encoded by the maximum response rate of a particular neuron and the tuning function is a peak function with the preferred magnitude represented at the maximum of discharge.
What is local coding?
A generic term for code values that are defined for a state or other political subdivision, or for a specific payer. This term is most commonly used to describe HCPCS Level III Codes, but also applies to state-assigned Institutional Revenue Codes, Condition Codes, Occurrence Codes, Value Codes, etc.
Which is better NLP or deep learning?
As we mentioned earlier, Deep Learning and NLP are both parts of a larger field of study, Artificial Intelligence. While NLP is redefining how machines understand human language and behavior, Deep Learning is further enriching the applications of NLP.