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National Institute of Standards and Technology artificial neural network (ann) architecture
Artificial Neural Network (Ann) Architecture, supplied by National Institute of Standards and Technology, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/neural+network+based+classifier/artificial+neural+networks++anns++based+on+the+ferroelectric+swcnt+transistor+array/pm40126172-62-2-28
Average 90 stars, based on 1 article reviews
artificial neural network (ann) architecture - by Bioz Stars, 2026-11
90/100 stars

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Article Title: Polymer synaptic transistors from memory to neuromorphic computing
Article Snippet: Neuromorphic engineering, inspired by the biological brain, is an emerging technique that uses electronic components to imitate the characteristics of biological neurons.. Neuromorphic electronics provide several advantages, including learning capability, low power consumption, and rapid response, which offer a possible solution to improve the performance of electronic systems.. Polymer-based field-effect transistors (FETs) with non-volatile memory characteristics have been considered promising devices for neuromorphic computing due to their unique electronic properties, excellent mechanical properties, solution processability, and biocompatibility.

other:

Article Title: Multifunctional Crystalline InGaSnO Phototransistor Exhibiting Photosensing and Photosynaptic Behavior Using Oxygen Vacancy Engineering.
Article Snippet: A multifunctional optoelectronic device implementing photodetector, photosynapse, and photomemory is of increasing attention for neuromorphic system.. This enables multiple devices to be replaced with a single device, which simplifies the structure of complex, highly integrated electronics.. Here, a multifunctional c-axis-aligned crystalline indium gallium tin oxide thin-film transistor (TFT) optoelectronic device is demonstrated.

Article Title: Enhanced Synaptic Behaviors in Chitosan Electrolyte-Based Electric-Double-Layer Transistors with Poly-Si Nanowire Channel Structures.
Article Snippet: Figure 5. (a) Analog change in channel conductance of film‐ and NW‐type chitosan EDL‐based syn‐ aptic transistors. (b) Conductance modulation interpreted by dividing Gmax by Gmin. (c) Schematic diagram of a fully connected artificial neural network (ANN) with three layers (input, hidden, and output) through synaptic weights for Modified National Institute of Standards and Technology (MNIST) simulations. (d) Simulated MNIST recognition rates by various numbers of hidden neu‐ rons and training epochs.

Article Title: Emerging photoelectric devices for neuromorphic vision applications: principles, developments, and outlooks
Article Snippet: Therefore, an artificial neural network (ANN) based on this device was constructed to mimic the recognition function of the visual system. shows the recognition accuracy for the handwritten digit dataset in Modified National Institute of Standards and Technology (MNIST).

Article Title: Defect-engineered 2D Bi 2 Se 3 -based broadband optoelectronic synapses with ultralow energy consumption for neuromorphic computing.
Article Snippet: An artificial neural network (ANN) architecture is simulated using the learning properties of our OES device to successfully realize a high recognition accuracy of 90.12% for MNIST (Modified National Institute of Standards and Technology) dataset handwritten digital images.



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