Author

Kaung Myat Naing

King Mongkut's Institute of Technology LadkrabangORCID 0000-0002-8067-4114Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Research Focus:cell type annotation· 2 Approach:deep learning· 2 Assay:imaging· 2 Research Focus:clustering· 1 Research Focus:differential expression· 1 Organism:human· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Santhad ChuwonginiD· 2 shared Siridech BoonsangiD· 2 shared Teerawat TongloyiD· 2 shared Veerayuth KittichaiiD· 2 shared Naphop Phatthamolrat· 1 shared Rangsan Jomtarak· 1 shared Theerakamol PengsakuliD· 1 shared

Activity by Year

2021-2021 · peak 2/yr

Co-Author Collaboration Network

7 top collaborators · 21 mutual co-author links

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2 shared papersBioinformatics

Santhad ChuwonginORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintAug 4, 2021

The Evaluation of Acute Myeloid Leukaemia (AML) Blood Cell Detection Models Using Different YOLO Approaches

Kaung Myat Naing, Veerayuth Kittichai, Teerawat Tongloy…·Siridech Boonsang

This paper evaluates YOLO models for detecting AML blast cells in blood images, finding YOLOv3 performs best with over 92% precision and sensitivity.

5 citations

𝕏 PostBluesky

BioinformaticsbioRxivPreprintJul 23, 2021

Performance of Deep Convolutional Neural Network Approaches and Human Level in Detecting Mosquito Species

Rangsan Jomtarak, Veerayuth Kittichai, Theerakamol Pengsakul…·Siridech Boonsang

The paper evaluates YOLO v3 for mosquito species classification, achieving high accuracy and sensitivity, and compares model performance with entomologist annotations.

3 citations

imagingdeep learning

𝕏 PostBluesky