Kernel Application of the Stacked Crossbar Array Composed of Self‐Rectifying Resistive Switching Memory for Convolutional Neural Networks
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
Online-Ressource
- Language
-
Englisch
- Bibliographic citation
-
Kernel Application of the Stacked Crossbar Array Composed of Self‐Rectifying Resistive Switching Memory for Convolutional Neural Networks ; volume:2 ; number:2 ; year:2020 ; extent:10
Advanced intelligent systems ; 2, Heft 2 (2020) (gesamt 10)
- Creator
-
Kim, Yumin
Kim, Jihun
Kim, Seung Soo
Kwon, Young Jae
Kim, Gil Seop
Jeon, Jeong Woo
Kwon, Dae Eun
Yoon, Jung Ho
Hwang, Cheol Seong
- DOI
-
10.1002/aisy.201900116
- URN
-
urn:nbn:de:101:1-2022062909585140407757
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
15.08.2025, 7:20 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Kim, Yumin
- Kim, Jihun
- Kim, Seung Soo
- Kwon, Young Jae
- Kim, Gil Seop
- Jeon, Jeong Woo
- Kwon, Dae Eun
- Yoon, Jung Ho
- Hwang, Cheol Seong
Other Objects (12)
Stacked device structures for resistive memory and logic
Resistive Switching in Memristors Based on Artificially Stacked Chemical-Vapor-Deposited Hexagonal-Boron Nitride
Two-stage multi-dimensional convolutional stacked autoencoder network model for hyperspectral images classification
An end-to-end graph convolutional kernel support vector machine
Condition Monitoring using Domain-Adversarial Networks with Convolutional Kernel Features
A hybrid stacked ensemble and Kernel SHAP-based model for intelligent cardiotocography classification and interpretability
A Sliding‐Kernel Computation‐In‐Memory Architecture for Convolutional Neural Network
Inherently interpretable position-aware convolutional motif kernel networks for biological sequencing data
THE LARGE-SCALE WILDFIRE SPREAD PREDICTION USING A MULTI-KERNEL CONVOLUTIONAL NEURAL NETWORK
Highly Stable Forming‐Free Bipolar Resistive Switching in Cu Layer Stacked Amorphous Carbon Oxide: Transition between C C Bonding Complexes
Using spreadsheets to produce stacked histogram, stacked line and spindle charts
Fully Binarized Graph Convolutional Network Accelerator Based on In‐Memory Computing with Resistive Random‐Access Memory
Stacked device structures for resistive memory and logic
Resistive Switching in Memristors Based on Artificially Stacked Chemical-Vapor-Deposited Hexagonal-Boron Nitride
Two-stage multi-dimensional convolutional stacked autoencoder network model for hyperspectral images classification
An end-to-end graph convolutional kernel support vector machine
Condition Monitoring using Domain-Adversarial Networks with Convolutional Kernel Features
A hybrid stacked ensemble and Kernel SHAP-based model for intelligent cardiotocography classification and interpretability
A Sliding‐Kernel Computation‐In‐Memory Architecture for Convolutional Neural Network
Inherently interpretable position-aware convolutional motif kernel networks for biological sequencing data
THE LARGE-SCALE WILDFIRE SPREAD PREDICTION USING A MULTI-KERNEL CONVOLUTIONAL NEURAL NETWORK
Highly Stable Forming‐Free Bipolar Resistive Switching in Cu Layer Stacked Amorphous Carbon Oxide: Transition between C C Bonding Complexes
Using spreadsheets to produce stacked histogram, stacked line and spindle charts
Fully Binarized Graph Convolutional Network Accelerator Based on In‐Memory Computing with Resistive Random‐Access Memory
Stacked device structures for resistive memory and logic
Resistive Switching in Memristors Based on Artificially Stacked Chemical-Vapor-Deposited Hexagonal-Boron Nitride
Two-stage multi-dimensional convolutional stacked autoencoder network model for hyperspectral images classification
An end-to-end graph convolutional kernel support vector machine
Condition Monitoring using Domain-Adversarial Networks with Convolutional Kernel Features
A hybrid stacked ensemble and Kernel SHAP-based model for intelligent cardiotocography classification and interpretability
A Sliding‐Kernel Computation‐In‐Memory Architecture for Convolutional Neural Network
Inherently interpretable position-aware convolutional motif kernel networks for biological sequencing data
THE LARGE-SCALE WILDFIRE SPREAD PREDICTION USING A MULTI-KERNEL CONVOLUTIONAL NEURAL NETWORK
Highly Stable Forming‐Free Bipolar Resistive Switching in Cu Layer Stacked Amorphous Carbon Oxide: Transition between C C Bonding Complexes
Using spreadsheets to produce stacked histogram, stacked line and spindle charts