Handcrafted features vs deep-learned features: Hermite Polynomial Classification of Liver Images-Reference-Cited by-同舟云学术

Handcrafted features vs deep-learned features: Hermite Polynomial Classification of Liver Images

Published:2023-06 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 36th International Symposium on Computer-Based Medical Systems (CBMS)
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Author:

Pereira Danilo C.¹,Longo Leonardo C.²,Tosta Thaína A. A.³,Martins Alessandro S.⁴,Silva Adriano B.¹,Rozendo Guilherme B.²,Roberto Guilherme F.⁵,Lumini Alessandra⁶,Neves Leandro A.²,do Nascimento Marcelo Z.¹

Affiliation:

1. Federal University of Uberlândia (UFU),Faculty of Computer Science (FACOM),Brazil

2. São Paulo State University (UNESP),Department of Computer Science and Statistics (DCCE),Brazil

3. Science and Technology Institute, Federal University of São Paulo (UNIFESP),Brazil

4. Federal Institute of Triângulo Mineiro (IFTM),Brazil

5. University of Porto (FEUP),Faculty of Engineering,Portugal

6. University of Bologna,Department of Computer Science and Engineering (DISI),Italy

Funder

National Council for Scientific and Technological Development CNPq

State of Minas Gerais Research Foundation - FAPEMIG

São Paulo Research Foundation - FAPESP

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10178426/10178704/10178873.pdf?arnumber=10178873

Reference33 articles.

1. Colour Feature Extraction and Polynomial Algorithm for Classification of Lymphoma Images

2. Generalized Hermite kernel function for support vector machine classifications

3. AGEMAP: A Gene Expression Database for Aging in Mice

4. Classification of lymphomas images with polynomial strategy: An application with Ridge regularization

5. Imbalance accuracy metric for model selection in multi-class imbalance classification problems

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