P
Panomkhawn Riyamongkol
Researcher at Naresuan University
Publications - 22
Citations - 493
Panomkhawn Riyamongkol is an academic researcher from Naresuan University. The author has contributed to research in topics: Computer science & Convolutional neural network. The author has an hindex of 7, co-authored 19 publications receiving 361 citations. Previous affiliations of Panomkhawn Riyamongkol include University of Miami.
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Journal ArticleDOI
Albumin Therapy of Transient Focal Cerebral Ischemia In Vivo Analysis of Dynamic Microvascular Responses
Ludmila Belayev,Elisabeth Pinard,Helene Nallet,Jacques Seylaz,Yitao Liu,Panomkhawn Riyamongkol,Weizhao Zhao,Raul Busto,Myron D. Ginsberg +8 more
TL;DR: These results reveal a beneficial effect of albumin therapy in reversing stagnation, thrombosis, and corpuscular adherence within cortical venules in the reperfusion phase after focal ischemia and support its utility in the treatment of acute ischemic stroke.
Journal ArticleDOI
Experimental Intracerebral Hemorrhage in the Mouse Histological, Behavioral, and Hemodynamic Characterization of a Double-Injection Model
Ludmila Belayev,Isabel Saul,Karell Curbelo,Raul Busto,Andrey Belayev,Yongbo Zhang,Panomkhawn Riyamongkol,Weizhao Zhao,Myron D. Ginsberg +8 more
TL;DR: The present ICH model in mice produces a consistent neurological deficit, hypoperfusion, hematoma volume, and brain swelling and should be useful for the evaluation of pharmaceutical therapies.
Proceedings ArticleDOI
Fire detection in the buildings using image processing
TL;DR: In this article, a fire detection system based on light detection and analysis is proposed, which uses HSV and YCbCr color models with given conditions to separate orange, yellow, and high brightness light from background and ambient light.
Journal ArticleDOI
Real-time Bhutanese license plate localization using YOLO
TL;DR: This paper presents the real-time Bhutanese license plate (LP) localization using YOLO (You Only Look Once) to eliminate the false positives generated by the signboards as they look similar to LPs.
Proceedings ArticleDOI
Flower recognition system based on image processing
TL;DR: The flower recognition system based on image processing uses edge and color characteristics of flower images to classify flowers and the accuracy of this system is more than 80%.