Complex Texture Features Learned by Applying Randomized Neural Network on Graphs-Reference-Cited by-同舟云学术

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Complex Texture Features Learned by Applying Randomized Neural Network on Graphs

Published:2022-04-19 Issue: Volume: Page:
ISSN:
Container-title:2022 Eleventh International Conference on Image Processing Theory, Tools and Applications (IPTA)
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Author:

Zielinski Kallil M. C.¹,Ribas Lucas C.¹,Scabini Leonardo F. S.¹,Bruno Odemir M.¹

Affiliation:

1. São Carlos Institute of Physics, University of São Paulo,São Carlos,SP,Brazil

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9784103/9784113/09784123.pdf?arnumber=9784123

Reference28 articles.

1. Improved texture image classification through the use of a corrosion-inspired cellular automaton

2. Texture analysis and classification: A complex network-based approach

3. Mul-tilayer complex network descriptors for color-texture characterization;scabini;ArXiv Preprint,2018

4. Texture recognition based on diffusion in networks

5. Analyzing and modeling real-world phenomena with complex networks: a survey of applications

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1. Fractal pooling: A new strategy for texture recognition using convolutional neural networks;Expert Systems with Applications;2024-06

2. A New Approach to Learn Spatio-Spectral Texture Representation with Randomized Networks: Application to Brazilian Plant Species Identification;Communications in Computer and Information Science;2024

3. A randomized network approach to multifractal texture descriptors;Information Sciences;2023-11

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