Statements (56)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
artificial neuron
|
| gptkbp:are |
non-linear
discrete theoretical constructs used in robotics foundational in cognitive science binary classifiers simplified models of biological neurons threshold logic units used in pattern recognition |
| gptkbp:basedOn |
binary logic
|
| gptkbp:canLeadTo |
image processing
natural language processing data mining signal processing |
| gptkbp:developedBy |
gptkb:Warren_McCulloch
gptkb:Walter_Pitts |
| gptkbp:formFactor |
artificial intelligence
|
| gptkbp:hasRelatedPatent |
machine learning
|
| https://www.w3.org/2000/01/rdf-schema#label |
McCulloch-Pitts neurons
|
| gptkbp:influencedBy |
Boolean algebra
|
| gptkbp:inspiredBy |
biological neural networks
|
| gptkbp:introduced |
1943
|
| gptkbp:isCounteredBy |
graphs
supervised learning unsupervised learning |
| gptkbp:isUsedFor |
automate tasks
improve healthcare systems activation functions model complex systems detect anomalies optimize processes perform classification tasks perform regression tasks predict outcomes solve optimization problems analyze data model decision making other neurons enhance decision support systems enhance security systems assist in scientific research create intelligent agents create neural networks develop autonomous systems drive innovation in technology facilitate learning algorithms improve user interfaces support financial modeling support recommendation systems |
| gptkbp:learnsMove |
from data
|
| gptkbp:mayHave |
logical functions
logical circuits |
| gptkbp:model |
neuron behavior
|
| gptkbp:usedIn |
neural networks
computational models |