Category:Artificial neural networks
Jump to navigation
Jump to search
computational model used in machine learning, based on connected, hierarchical functions | |||||
Upload media | |||||
Pronunciation audio | |||||
---|---|---|---|---|---|
Subclass of |
| ||||
Facet of | |||||
Has part(s) |
| ||||
Different from | |||||
| |||||
![]() |
English: An artificial neural network (ANN), often just called a "neural network" (NN), is a mathematical model or computational model based on biological neural networks.
Subcategories
This category has the following 14 subcategories, out of 14 total.
A
- Activation functions (33 F)
B
- Balanced networks (15 F)
- Boltzmann machines (6 F)
C
G
H
- Hopfield net (1 P, 6 F)
I
N
- Neural networks (computer) (30 F)
P
- Perceptrons (57 F)
S
- Self-organizing maps (23 F)
- SpiNNaker (3 F)
Pages in category "Artificial neural networks"
The following 3 pages are in this category, out of 3 total.
Media in category "Artificial neural networks"
The following 200 files are in this category, out of 251 total.
(previous page) (next page)- 060728b unnormalized basis function phi.png 699 × 579; 7 KB
- 060731 logistic map time series 2.png 699 × 466; 9 KB
- 060803 normalized radial basis functions.png 700 × 472; 4 KB
- 060804 3 normalized basis functions.png 700 × 472; 6 KB
- 060804 4 normalized basis functions.png 700 × 472; 7 KB
- 060808 control of logistic map.png 1,067 × 633; 11 KB
- 060808 control of logistic map.svg 1,334 × 791; 278 KB
- 1D Convolution.png 321 × 310; 11 KB
- 1D Convolutional Neural Network feed forward example.png 661 × 301; 31 KB
- 3 filters in a Convolutional Neural Network.gif 960 × 720; 182 KB
- 3 Normalized radial basis functions.svg 460 × 422; 2 KB
- 3 кл.png 347 × 135; 21 KB
- 3ddddd.png 367 × 239; 22 KB
- 4 Normalized radial basis functions.svg 460 × 422; 3 KB
- 4 кл.png 327 × 144; 22 KB
- A-neural-network-based-exploratory-learning-and-motor-planning-system-for-co-robots-Video1.ogv 32 s, 854 × 480; 3.27 MB
- A-neural-network-based-exploratory-learning-and-motor-planning-system-for-co-robots-Video2.ogv 42 s, 854 × 480; 15.03 MB
- A-neural-network-based-exploratory-learning-and-motor-planning-system-for-co-robots-Video3.ogv 38 s, 854 × 480; 7.26 MB
- A-NFHB-Class-Architecture.jpg 600 × 489; 17 KB
- A Biologically-Inspired Neural Network Architecture for Image Processing (IA abiologicallyins1094530625).pdf 1,275 × 1,650, 160 pages; 5.52 MB
- Activation gelu.png 1,200 × 800; 65 KB
- ActivationFunctions.svg 1,058 × 606; 293 KB
- Adaline flow chart.gif 393 × 605; 4 KB
- Adaline modell-A-svg.svg 600 × 410; 14 KB
- Adaline modell.png 438 × 283; 14 KB
- Adaline ukr.JPG 393 × 605; 17 KB
- Adaline.jpg 482 × 318; 27 KB
- Adaptive-Fast-Walking-in-a-Biped-Robot-under-Neuronal-Control-and-Learning-pcbi.0030134.sv001.ogv 0.0 s, 312 × 240; 4.93 MB
- Adaptive-Fast-Walking-in-a-Biped-Robot-under-Neuronal-Control-and-Learning-pcbi.0030134.sv002.ogv 1 min 46 s, 312 × 240; 12.29 MB
- AHaH-Computing-From-Metastable-Switches-to-Attractors-to-Machine-Learning-pone.0085175.s001.ogv 1 min 19 s, 288 × 318; 9.9 MB
- AHaH-Computing-From-Metastable-Switches-to-Attractors-to-Machine-Learning-pone.0085175.s002.ogv 1 min 13 s, 304 × 318; 11.25 MB
- AHaH-Computing-From-Metastable-Switches-to-Attractors-to-Machine-Learning-pone.0085175.s003.ogv 48 s, 296 × 320; 3.36 MB
- AHaH-Computing-From-Metastable-Switches-to-Attractors-to-Machine-Learning-pone.0085175.s004.ogv 36 s, 296 × 318; 891 KB
- AHaH-Computing-From-Metastable-Switches-to-Attractors-to-Machine-Learning-pone.0085175.s005.ogv 40 s, 494 × 512; 5.69 MB
- AHaH-Computing-From-Metastable-Switches-to-Attractors-to-Machine-Learning-pone.0085175.s006.ogv 58 s, 496 × 512; 7.55 MB
- AHaH-Computing-From-Metastable-Switches-to-Attractors-to-Machine-Learning-pone.0085175.s007.ogv 56 s, 492 × 514; 6.86 MB
- AHaH-Computing-From-Metastable-Switches-to-Attractors-to-Machine-Learning-pone.0085175.s008.ogv 56 s, 492 × 512; 6.74 MB
- AHaH-Computing-From-Metastable-Switches-to-Attractors-to-Machine-Learning-pone.0085175.s009.ogv 1 min 29 s, 494 × 512; 10.25 MB
- Alexnet.svg 698 × 1,851; 30 KB
- Algorithm 2 of the instant Learning Ratio(ILR) ML.png 734 × 873; 132 KB
- ANFIS - de.svg 1,590 × 731; 155 KB
- Ann dependency (graph).svg 178 × 127; 151 KB
- Ann dependency graph.png 353 × 253; 4 KB
- ANN neuron.svg 1,720 × 1,133; 94 KB
- ANN-ComputerScience-AI Relation.png 298 × 191; 4 KB
- Architecture algoHJ.PNG 617 × 319; 12 KB
- Architektura bidirektní paměti.png 454 × 426; 102 KB
- Architektury neuronové sítě.png 430 × 353; 53 KB
- Art schéma.png 589 × 425; 58 KB
- ART.png 1,024 × 780; 138 KB
- ART.svg 744 × 567; 33 KB
- Artificial imagination silveira.jpg 850 × 1,129; 841 KB
- Artificial Neural Network Example.png 3,840 × 2,880; 292 KB
- Artificial neural network image recognition.png 693 × 600; 34 KB
- Artificial neural network pso.png 1,625 × 1,157; 366 KB
- Artificial Neural Network with Chip.jpg 2,000 × 1,600; 2.59 MB
- Artificial Neural Network with Chip.png 1,257 × 943; 1.9 MB
- Artificial Neural Network.gif 960 × 720; 88 KB
- Artificial neural network.png 800 × 380; 19 KB
- Artificial neuron 2.gif 845 × 458; 11 KB
- Artificial Neuron And.png 437 × 249; 319 KB
- Artificial Neuron Not.png 456 × 181; 242 KB
- Artificial neuron or.png 437 × 259; 332 KB
- Artificial neuron or.svg 437 × 255; 16 KB
- Artificial Neuron Scheme.png 681 × 502; 21 KB
- Artificial neuron-2.gif 845 × 458; 11 KB
- Artificial neuron.png 272 × 187; 2 KB
- ARTMAP.png 1,024 × 582; 120 KB
- ARTMAP.svg 744 × 423; 74 KB
- Autoencoder structure uk.png 677 × 506; 39 KB
- Autoencoder structure.png 677 × 506; 48 KB
- Autoenkodér.png 515 × 340; 41 KB
- Back Propagation Example.svg 770 × 360; 269 KB
- Backprogation neural networks.png 458 × 496; 26 KB
- Backpropagation.png 403 × 319; 51 KB
- Back-propagation neural networks in adaptive control of unknown nonlinear systems. (IA backpropagationn00teoc).pdf 1,168 × 1,581, 124 pages; 5.77 MB
- Backpropagation neural network for noise cancellation applied to the NUWES test ranges (IA backpropagationn00well).pdf 1,181 × 1,606, 86 pages; 4.01 MB
- Back-propagation neural networks in adaptive control of unknown nonlinear systems (IA backpropagationn1094530830).pdf 1,275 × 1,650, 89 pages; 15.36 MB
- Bidirectional recurrent neural network.png 635 × 593; 117 KB
- Biological-neural-networks.jpg 600 × 385; 130 KB
- Breast ANN.svg 545 × 808; 25 KB
- CapaOculta.png 247 × 220; 27 KB
- Colored neural network es.svg 296 × 356; 220 KB
- Competitive neural network architecture.png 304 × 329; 14 KB
- Computer.Science.AI.Neuron.AND.svg 725 × 788; 19 KB
- Computer.Science.AI.Neuron.OR.svg 725 × 788; 20 KB
- Computer.Science.AI.Neuron.svg 675 × 300; 20 KB
- Computer.Science.AI.Neuron.XOR.svg 725 × 788; 15 KB
- Concept of instant learning ratio in Machine Learning.png 719 × 336; 40 KB
- Conformadorhaces.JPG 558 × 424; 28 KB
- Convolutional Neural Network NeuralNetworkFeatureLayers.gif 960 × 720; 127 KB
- Convolutional Neural Network NeuralNetworkFilter.gif 960 × 720; 96 KB
- Convolutional Neural Network with Color Image Filter.gif 960 × 720; 129 KB
- Convolutional Neural Network.gif 960 × 720; 50 KB
- Convolutional-neural-network-polyanalyst-flowchart-example.png 561 × 190; 20 KB
- Cortex contrast.png 406 × 255; 11 KB
- DAGUI.jpg 391 × 246; 35 KB
- DAP.png 569 × 535; 24 KB
- DavidRumelhart-IJCNNseattle1991-07-08.jpg 2,217 × 2,560; 1.73 MB
- Deep belief net.svg 230 × 345; 3 KB
- Deep Learning.jpg 1,239 × 1,012; 341 KB
- DeepIngisht FeatureMapping.jpg 1,104 × 900; 179 KB
- DeepInsight method to transform non-image data to 2D image for convolutional neural network architecture.pdf 1,239 × 1,629, 7 pages; 1.78 MB
- DeepInsight Pipeline.jpg 1,200 × 425; 143 KB
- DeepInsight RevealingPatterns.jpg 3,809 × 3,312; 1.75 MB
- DeepQA.svg 1,630 × 815; 16 KB
- Diagram BRNN RNN Compare.png 1,626 × 838; 184 KB
- Diagram of a McCulloch-Pitts-cell.svg 569 × 250; 8 KB
- Diagrama de red neuronal artificial.png 7,296 × 3,986; 6.79 MB
- DiagramJordanNet deutsch.png 1,666 × 809; 66 KB
- DiagramTDNN deutsch.png 1,598 × 2,383; 130 KB
- DiagramTDNN english.png 1,454 × 2,383; 116 KB
- Differentiable Neural Computer.png 1,000 × 881; 24 KB
- Differentiable neural computer.svg 649 × 284; 242 KB
- Differentiable Neural Computer.svg 177 × 156; 15 KB
- Distributed ART model (dART).png 908 × 768; 99 KB
- Distributed representation.svg 800 × 246; 15 KB
- DNC training recall task.gif 919 × 459; 8.21 MB
- Elman srnn.png 673 × 745; 52 KB
- Elman.svg 716 × 578; 18 KB
- Energy landscape.png 1,581 × 560; 26 KB
- Expressivity matrix of an artificial binary neuron.png 2,048 × 2,048; 276 KB
- Faces example (neural-enhance).png 1,280 × 667; 666 KB
- Filtrace šumu.png 301 × 122; 10 KB
- From-grid-cells-and-visual-place-cells-to-multimodal-place-cell-a-new-robotic-architecture-Movie1.ogv 5 min 3 s, 768 × 576; 20.21 MB
- Fully connected neural network.svg 700 × 600; 8 KB
- Gated Recurrent Unit, base type.svg 780 × 390; 12 KB
- Gated Recurrent Unit, type 1.svg 780 × 390; 12 KB
- Gated Recurrent Unit, type 2.svg 780 × 390; 11 KB
- Gated Recurrent Unit, type 3.svg 780 × 390; 11 KB
- Gated Recurrent Unit.svg 1,594 × 709; 49 KB
- Generlized Regression Neural Network (GRNN).png 1,468 × 802; 66 KB
- GPT2-talks-about-GPT2.png 1,902 × 943; 178 KB
- Grossbergova síť.png 222 × 252; 17 KB
- HopfildaTikls.png 423 × 388; 4 KB
- Infinitely wide neural network.webm 8.0 s, 1,920 × 1,080; 9.41 MB
- Instant Learning Ratio - Machine Learning Idea.png 671 × 388; 31 KB
- Linking ImageNet WordNet Synsets with Wikidata - Figure 2a.jpg 636 × 471; 43 KB
- Linking ImageNet WordNet Synsets with Wikidata - Figure 2b.jpg 638 × 478; 57 KB
- Localist (one-hot) representation.svg 800 × 246; 17 KB
- Long Short Term Memory uk.png 793 × 453; 20 KB
- Long Short Term Memory.png 793 × 453; 30 KB
- Long Short-Term Memory.svg 1,594 × 709; 52 KB
- Malmberg Neural Net Circuit.png 664 × 606; 45 KB
- Microwave diffractive ANN.png 2,326 × 998; 1.9 MB
- Model aktivace neuronu.png 238 × 221; 5 KB
- Model synapse.png 339 × 110; 2 KB
- Multi-Layer Neural Network-Vector-Blank.svg 815 × 390; 6 KB
- Multi-Layer Neural Network-Vector.svg 957 × 567; 7 KB
- Multilayer Neural Network.png 531 × 305; 18 KB
- Multilayer Perceptron with one hidden layer.svg 293 × 248; 40 KB
- MultiLayerNeuralNetwork deutsch.png 620 × 347; 44 KB
- MultiLayerNeuralNetwork english.png 620 × 347; 43 KB
- MultiLayerNeuralNetwork.png 620 × 278; 38 KB
- MultiLayerNeuralNetworkBigger english.png 904 × 356; 50 KB
- MultiLayerPerceptron.png 1,061 × 487; 72 KB
- MultiLayerPerceptron.svg 1,052 × 744; 23 KB
- Neural Abstraction Pyramid.jpg 1,343 × 782; 253 KB
- Neural Designer logo.png 697 × 156; 16 KB
- Neural network bottleneck achitecture.svg 1,052 × 744; 48 KB
- Neural network bottleneck achitecture2.svg 1,052 × 744; 50 KB
- Neural Network Dropout.svg 986 × 416; 115 KB
- Neural Network Identifies Stars.jpg 1,545 × 1,200; 110 KB
- Neural network.svg 600 × 400; 1 KB
- NeuralNetwork.png 1,278 × 861; 105 KB
- Neuro-fuzzy.jpg 611 × 478; 32 KB
- Neuron comparison uk.png 426 × 362; 53 KB
- Neuron comparison.png 426 × 362; 72 KB
- Neuron McCullocha-Pittsa.svg 410 × 230; 27 KB
- Neuronal Network scheme.JPG 506 × 278; 19 KB
- NeuronenTypenHLim.png 25 × 25; 758 bytes
- NeuronenTypenInput.png 25 × 25; 585 bytes
- NeuronenTypenPWL.png 25 × 25; 737 bytes
- NeuronenTypenSig.png 25 × 25; 747 bytes
- NeuronModel deutsch.svg 5,450 × 2,580; 9 KB
- Nicht-Neuron.png 646 × 458; 18 KB
- Nicht-Neuron.svg 194 × 138; 2 KB
- NM 6408 neural network during the "Armiya 2022" exhibition.jpg 2,734 × 4,886; 3.56 MB
- Nntraintool.JPG 478 × 657; 77 KB
- Normalized basis functions.png 699 × 579; 7 KB
- Normalized radial basis functions.svg 460 × 422; 2 KB
- Närvivõrgu mudel.png 605 × 589; 44 KB
- Oder-Neuron.png 646 × 458; 29 KB
- Oder-Neuron.svg 194 × 138; 4 KB
- Optical logic gate with diffractive neural network.png 2,440 × 900; 1.4 MB
- PaulWerbos-IJCNNseattle1991-07-08.jpg 2,343 × 2,934; 2.04 MB
- PDPmodel.png 1,681 × 527; 148 KB
- Peephole Long Short-Term Memory.svg 542 × 298; 49 KB
- Perceptron 1.webm 4 min 53 s, 292 × 300; 6.01 MB
- PerceptronBack4.png 371 × 300; 10 KB
- Perzeptrons Bias.png 362 × 162; 5 KB
- PhysRevC.99.025204.pdf 1,227 × 1,650, 14 pages; 581 KB
- Pipe-line of GNN.png 1,596 × 807; 120 KB
- Plot of Loss Functions.png 1,920 × 870; 47 KB
- Pásma citlivosti.png 749 × 722; 187 KB
- RadBasFunction.JPG 672 × 405; 14 KB
- Radial funktion network.svg 465 × 390; 8 KB