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Non‐linear coupled CNN models for multiscale image analysis
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Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/(sici)1097-007x(199807/08)26:4<375::aid-cta19>3.0.co;2-#openalex-snapshot
CNN‐based difference‐controlled adaptive non‐linear image filters
inferredcites →https://doi.org/10.1002/cta.202openalex-snapshot
CNN architectures for constrained diffusion based locally adaptive image processing
inferredcites →https://doi.org/10.1007/3-540-63167-4_37openalex-snapshot
A review of nonlinear diffusion filtering
inferredcites →https://doi.org/10.1007/3-540-76076-8_123openalex-snapshot
Nonlinear diffusion scale-spaces: From the continuous to the discrete setting
inferredcites →https://doi.org/10.1007/bf00375127openalex-snapshot
Axioms and fundamental equations of image processing
inferredcites →https://doi.org/10.1017/cbo9780511754494openalex-snapshot
Cellular Neural Networks and Visual Computing
inferredcites →https://doi.org/10.1108/ir.1999.04926fae.001openalex-snapshot
Lecture Notes in Computer Science 1205
inferredcites →https://doi.org/10.1109/101.526876openalex-snapshot
CNN universal chips crank up the computing power
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Cellular neural networks: applications
inferredcites →https://doi.org/10.1109/34.56205openalex-snapshot
Scale-space and edge detection using anisotropic diffusion
inferredcites →https://doi.org/10.1137/0729012openalex-snapshot
Image Selective Smoothing and Edge Detection by Nonlinear Diffusion
inferredcites →https://doi.org/10.1142/s0218127402005868openalex-snapshot
CNN DYNAMICS REPRESENTS A BROADER CLASS THAN PDEs
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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On the implementation of linear diffusion in transconductance‐based cellular nonlinear networks
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Experimental Dynamics Observed in a Configurable Complex Network of Chaotic Oscillators
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Experiments on Clustering and Synchronous Patterns in a Configurable Network of Chaotic Oscillators
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A CNN-based computational algorithm for nonlinear image diffusion problem
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Markov chain network training and conservation law approximations: Linking microscopic and macroscopic models for evolution
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Architectures for nanoscale hybrid computing systems
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Identification of EEG signals in epilepsy by cell outputs of Reaction-Diffusion Networks
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Solving stiff ordinary differential equations and partial differential equations using analog computing based on cellular neural networks
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CNN-based algorithm for drusen identification
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An Innovative Method for Thermal Characterization of Automotive Electronic Devices Based on CNNs
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COMPLEXITY INDEX OF OUTER-TOTALISTIC BINARY CELLULAR AUTOMATA WITH ARBITRARY DIMENSION AND NEIGHBORHOOD
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Improved Intelligent Learning Filter in Deep Learning Systems and Its Application in Traffic Object Detection
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An Ensemble of Prediction and Learning Mechanism for Improving Accuracy of Anomaly Detection in Network Intrusion Environments
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Linking Microscopic and Macroscopic Models for Evolution: Markov Chain Network Training and Conservation Law Approximations
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Identifikationsverfahren zur Analyse von EEG-Signalen bei Epilepsie mit Reaktions-Diffusions Netzwerken
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