On the public citation graph
Topographic cellular active contour techniques: theory, implementations and comparisons
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/(sici)1097-007x(199901/02)27:1<171::aid-cta47>3.0.co;2-xopenalex-snapshot
CNN-based spatio-temporal nonlinear filtering and endocardial boundary detection in echocardiography
inferredcites →https://doi.org/10.1002/cta.302openalex-snapshot
Pixel‐level snakes on the CNNUM: algorithm design, on‐chip implementation and applications
inferredcites →https://doi.org/10.1016/s0262-8856(02)00153-1openalex-snapshot
Cellular neural networks and active contours: a tool for image segmentation
inferredcites →https://doi.org/10.1023/a:1008153320440openalex-snapshot
Computing with Front Propagation: Active Contour And Skeleton Models In Continuous-Time CNN
inferredcites →https://doi.org/10.1023/a:1008161522257openalex-snapshot
A Nonlinear Wave Metric and its CNN Implementation for Object Classification
inferredcites →https://doi.org/10.1109/34.368173openalex-snapshot
Shape modeling with front propagation: a level set approach
inferredcites →https://doi.org/10.1109/42.481439openalex-snapshot
Biased motion-adaptive temporal filtering for speckle reduction in echocardiography
inferredcites →https://doi.org/10.1109/42.500138openalex-snapshot
A multiple active contour model for cardiac boundary detection on echocardiographic sequences
inferredcites →https://doi.org/10.1109/5.915376openalex-snapshot
Interconnect limits on gigascale integration (GSI) in the 21st century
inferredcites →https://doi.org/10.1109/82.222815openalex-snapshot
The CNN universal machine: an analogic array computer
inferredcites →https://doi.org/10.1109/icecs.1998.813304openalex-snapshot
A 64×64 CNN universal chip with analog and digital I/O
inferredcites →https://doi.org/10.1109/tbme.2002.1028423openalex-snapshot
Real-time speckle reduction and coherence enhancement in ultrasound imaging via nonlinear anisotropic diffusion
inferredcites →https://doi.org/10.1109/tcsi.2004.827621openalex-snapshot
ACE16k: The Third Generation of Mixed-Signal SIMD-CNN ACE Chips Toward VSoCs
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/cta.1823openalex-snapshot
Implementation of cellular genetic algorithms on a CNN chip: Simulations and experimental results
inferred← citeshttps://doi.org/10.1002/cta.361openalex-snapshot
Object comparison using PDE‐based wave metric on cellular neural networks
inferred← citeshttps://doi.org/10.1002/cta.451openalex-snapshot
On global exponential stability of standard and full‐range CNNs
inferred← citeshttps://doi.org/10.1002/cta.679openalex-snapshot
Asynchronous cellular logic network as a co‐processor for a general‐purpose massively parallel array
inferred← citeshttps://doi.org/10.1007/978-3-540-88464-4_9openalex-snapshot
Visual Algorithms for Cognition
inferred← citeshttps://doi.org/10.1109/cnna.2006.341614openalex-snapshot
CNNOPT: Learning dynamics and CNN chip-specific robustness
inferred← citeshttps://doi.org/10.1109/cnna.2006.341643openalex-snapshot
A Cellular Active Contours Algorithm Based on Region Evolution
inferred← citeshttps://doi.org/10.1109/cnna.2006.341646openalex-snapshot
Space-time Signature Analysis of 2D Echocardiograms Based on Topographic Cellular Active Contour Techniques
inferred← citeshttps://doi.org/10.1109/cnna.2006.341651openalex-snapshot
CNNUM-Based Methods Using Deformable Contours on Smooth Boundaries
inferred← citeshttps://doi.org/10.1109/cnna.2008.4588662openalex-snapshot
Implementing the grayscale wave metric on a cellular array processor chip
inferred← citeshttps://doi.org/10.1109/cnna.2010.5430256openalex-snapshot
Variational computing based segmentation methods for medical imaging by using CNN
inferred← citeshttps://doi.org/10.1109/tim.2009.2026619openalex-snapshot
An Innovative Method for Thermal Characterization of Automotive Electronic Devices Based on CNNs
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