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Wongthawat Liawrungrueang. Overcoming imbalanced data challenges in spinal disorder detection: an integrated YOLOv5 and CNNs approach with SMOTE. (). King Mongkut's University of Technology North Bangkok. Central Library. : , .
Overcoming imbalanced data challenges in spinal disorder detection: an integrated YOLOv5 and CNNs approach with SMOTE
Name: Wanchaloem Nadda
Organization :
Chiang Mai University. Faculty of Science
Email :
wanchaloem_n@cmu.ac.th
Name: Wararat Boonchieng
Organization :
The Prince Royals College
Email :
wararat.boonchieng@gmail.com
Organization :
University of Payao. School of Medicine
Email :
mint11871@hotmail.com
keyword:
YOLOv5
;
SMOTE
Abstract:
This paper outlines an innovative methodology
for the identification and categorization of spinal disorders, a
significant health concern that dramatically influences
individuals' well-being. The advanced procedure utilizes the
potent capabilities of the YOLOv5 object detection framework
and Convolutional Neural Networks (CNN) coupled with
Synthetic Minority Over-sampling Technique (SMOTE). This
combination adeptly addresses the challenges associated with
class imbalance in diagnosing spinal disorders. Employing these
techniques on the Burapha Spine Dataset, our model has
achieved success in pinpointing and classifying four distinct
spinal disorders, irrespective of their varied occurrence rates.
The approach focuses on detecting each vertebra separately and
then taking two neighboring vertebrae for spinal disorder
classification via a CNN model incorporating SMOTE
oversampling. As a result, this procedure considerably boosts
diagnostic precision in spinal disorders
King Mongkut's University of Technology North Bangkok. Central Library
Address:
BANGKOK
Email:
library@kmutnb.ac.th
Modified:
2024-04-24
Issued:
2024-04-24
บทความ/Article
application/pdf
BibliograpyCitation :
In Institute of Electrical and Electronics Engineers. The 27th International Computer Science and Engineering Conference 2023 (ICSEC 2023) (pp.425-428). Bangkok : Institute of Electrical and Electronics Engineers
eng
©copyrights King Mongkut's University of Technology North Bangkok
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ใช้เวลา
0.036852 วินาที
Wanchaloem Nadda
| Title | Contributor | Type |
|---|---|---|
| Overcoming imbalanced data challenges in spinal disorder detection: an integrated YOLOv5 and CNNs approach with SMOTE
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Wanchaloem Nadda;Wararat Boonchieng;Wongthawat Liawrungrueang | บทความ/Article |
Wararat Boonchieng
| Title | Contributor | Type |
|---|---|---|
| Overcoming imbalanced data challenges in spinal disorder detection: an integrated YOLOv5 and CNNs approach with SMOTE
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Wanchaloem Nadda;Wararat Boonchieng;Wongthawat Liawrungrueang | บทความ/Article |
Wongthawat Liawrungrueang
| Title | Contributor | Type |
|---|---|---|
| Overcoming imbalanced data challenges in spinal disorder detection: an integrated YOLOv5 and CNNs approach with SMOTE
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Wanchaloem Nadda;Wararat Boonchieng;Wongthawat Liawrungrueang | บทความ/Article |