แจ้งเอกสารไม่ครบถ้วน, ไม่ตรงกับชื่อเรื่อง หรือมีข้อผิดพลาดเกี่ยวกับเอกสาร ติดต่อที่นี่ ==>
หากไม่มีอีเมลผู้รับให้กรอก thailis-noc@uni.net.th
หากไม่มีอีเมลผู้รับให้กรอก thailis-noc@uni.net.th
Surapol Vorapatratorn. M-stock : automate photo assessment for enhancing student photography skills with deep learning. (). King Mongkut's University of Technology North Bangkok. Central Library. : , 2024.
M-stock : automate photo assessment for enhancing student photography skills with deep learning
Name: Nontawat Thongsibsong
Organization :
Mae Fah Luang University. School of Information Technology
Email :
Nontawat@mfu.ac.th
Name: Surapol Vorapatratorn
Organization :
Mae Fah Luang University. School of Information Technology
Email :
Surapol.vor@mfu.ac.th
LCSH:
Photography
-- Study and teaching
LCSH:
Image processing
-- Digital techniques
LCSH:
Artificial intelligence
Abstract:
Presently, digital photography courses are
being offered both in traditional university classrooms and
through online platforms. Evaluating students' work in these
courses, particularly when instructed by photography
experts, presents challenges, especially in larger classrooms
with numerous students. The difficulties include the inability
to promptly assess and provide feedback due to the volume of
work, leading to delays in meeting students' needs.
Consequently, students are unable to receive immediate
feedback on their submissions, causing a lag in their skill
development. To address this issue, we propose the M-Stock
system, an Automatic Photo Assessment for Enhancing
Student Photography Skills with Deep Learning. This system
operates as a web application and is compatible with all
platforms. It utilizes Convolutional Neural Networks (CNN)
for photo classification and evaluation. Through testing the
classification efficiency, the system demonstrated an average
accuracy of 97.18%, with an average classification speed of
46.1 milliseconds per image. This automation aims to
streamline the evaluation process, ensuring timely feedback
and fostering the timely development of students' abilities
King Mongkut's University of Technology North Bangkok. Central Library
Address:
BANGKOK
Email:
library@kmutnb.ac.th
Created:
2024
Modified:
2025-06-06
Issued:
2025-06-06
บทความ/Article
application/pdf
BibliograpyCitation :
In IEEE Thailand Section (IEEE Computer Society Thailand Chapter) and Prince of Songkla University. College of Computing. The 21st International Joint Conference on Computer Science and Software Engineering (JCSSE 2024)) (pp.508-513). Phuket : Prince of Songkla University
eng
©copyrights King Mongkut's University of Technology North Bangkok
RightsAccess:
ใช้เวลา
0.035843 วินาที
Nontawat Thongsibsong
| Title | Contributor | Type |
|---|---|---|
| M-stock : automate photo assessment for enhancing student photography skills with deep learning
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Nontawat Thongsibsong;Surapol Vorapatratorn | บทความ/Article |
Surapol Vorapatratorn
| Title | Contributor | Type |
|---|---|---|
| M-stock : automate photo assessment for enhancing student photography skills with deep learning
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Nontawat Thongsibsong;Surapol Vorapatratorn | บทความ/Article | |
| Online low-cost air quality monitoring system using LoRa-based communication
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Vittayasak Rujivorakul;Surapol Vorapatratorn | บทความ/Article |