Výsledky vyhledávání - "Suwimol Jungjit"

Akademický článek

Ensemble Feature Selection for Breast Cancer Classification using Microarray Data

Autor: Supoj Hengpraprohm, Suwimol Jungjit

Publikováno v: Inteligencia Artificial, Vol 23, Iss 65 (2020)

For breast cancer data classification, we propose an ensemble filter feature selection approach named ‘EnSNR’. Entropy and SNR evaluation functions are used to find the features (genes) for the EnSNR subset. A Genetic Algorithm (GA) generates the

Externí odkaz: https://doaj.org/article/1554d84cadb34475abb91b108a952860

Zobrazit plný text záznamu

Colour Characterization and Detection of Dry Chinese Sausage Casing Twist using Colour Image Analysis

Autor: CheeYuen Lam, Phaklen Ehkan, Suwimol Jungjit

Publikováno v: Journal of Physics: Conference Series. 1755:012050

Chinese sausage is traditional air-dry sausage that loved by the Chinese community around the globe. This sausage can be served alone after steam cook or cook with other ingredients to create other tasty Chinese delicacies. However, a manual hand cut

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::697a33d053d07040554f624bc0397b76
https://doi.org/10.1088/1742-6596/1755/1/012050

Zobrazit plný text záznamu

Real Time Detection of Object Blob Localization Application using 1-D Connected Pixel and Windowing Method on FPGA

Autor: CheeYuen Lam, R. A. A. Raof, Phaklen Ehkan, Suwimol Jungjit

Publikováno v: Journal of Physics: Conference Series. 1755:012054

Blob detection and localization is a common process used in the machine vision. Current existing blob detection method is using 2-dimensional kernel matrix which is higher in time consumption and also memory space. This study has proposed a dedicated

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::a8d87b2f984a639573039f39fbf8665b
https://doi.org/10.1088/1742-6596/1755/1/012054

Zobrazit plný text záznamu

A lexicographic multi-objective genetic algorithm for multi-label correlation-based feature selection

Autor: Suwimol Jungjit, Alex A. Freitas

Publikováno v: GECCO (Companion)

This paper proposes a new Lexicographic multi-objective Genetic Algorithm for Multi-Label Correlation-based Feature Selection (LexGA-ML-CFS), which is an extension of the previous single-objective Genetic Algorithm for Multi-label Correlation-based F

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c4a946580fe89527e2d12e68e3722c57
https://kar.kent.ac.uk/50175/1/GECCO-2015-Wksp-Jungjit-as-publ.pdf

Zobrazit plný text záznamu

Extending multi-label feature selection with KEGG pathway information for microarray data analysis

Autor: Suwimol Jungjit, J. Cinatl, Martin Michaelis, Alex A. Freitas

Publikováno v: CIBCB

We propose three approaches to extend our previous Multi-Label Correlation-based Feature Selection (ML-CFS) method with cancer-related KEGG pathway information, in order to select a better set of genes (features) for cancer microarray data classifica

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::82e00e10af58516e4a5b4d9e4c25e9be
https://doi.org/10.1109/cibcb.2014.6845501

Zobrazit plný text záznamu

Two Extensions to Multi-label Correlation-Based Feature Selection: A Case Study in Bioinformatics

Autor: Alex A. Freitas, Jindrich Cinatl, Martin Michaelis, Suwimol Jungjit

Publikováno v: SMC

This paper proposes two extensions to a Multi-Label Correlation Based Feature Selection Method (ML-CFS): (1) ML-CFS using the absolute value of the correlation coefficient in the equation for evaluating a candidate feature subset, and (2) ML-CFS usin

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::5633e64fb9aac32fa5cac501ad7d067c
https://doi.org/10.1109/smc.2013.262

Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání