แจ้งเอกสารไม่ครบถ้วน, ไม่ตรงกับชื่อเรื่อง หรือมีข้อผิดพลาดเกี่ยวกับเอกสาร ติดต่อที่นี่ ==>
หากไม่มีอีเมลผู้รับให้กรอก thailis-noc@uni.net.th
หากไม่มีอีเมลผู้รับให้กรอก thailis-noc@uni.net.th
Teepakorn Tosawadi. Automatic Rice plant disease evaluation method based on anomaly detection and deep learning. Master's Degree(Information and Communication Technology for Embedded System). Kasetsart University. Office of the University Library. : Kasetsart University, 2021.
Automatic Rice plant disease evaluation method based on anomaly detection and deep learning
Name: Teepakorn Tosawadi
Classification :.LCCS: TA1637
LCSH:
Image processing
LCSH:
Rice blast disease
Abstract:
In rice breeding process, the main barrier is disease scoring and evaluation. The conventional evaluation process is slow because of manual evaluation. Rice breeder has to evaluate disease resistance in rice individually. This time consuming and man laboring can be replaced with automatic process using deep learning technique. This work introduced a rice blast disease classification and localization on collected dataset using convolutional neural networks. Instead of classifying an image containing the entire rice plant, a proposed method performs a classification on multiple image sections selected from the defect region. This approach shows that a classification network can identify a disease from a bunch of small sections better than using a resized image of acquired as input image. In part of disease localization, a class activation map (CAM) is applied to multiple subimages to create a disease localization map. The CAM resulted in form of heatmap, where the heatmap shows the area corresponding to disease region. Then perform segmentation to obtain area indicating disease region and use for a roughly disease severity evaluation.
Kasetsart University. Office of the University Library
Address:
Bangkok
Email:
tdckulib@ku.ac.th
Name: Teerasit Kasetkasem
Role:
Thesis Advisor
Name: Teera Phatrapornnant
Role:
Thesis CO-Advisor
Name: Itsuo Kumazawa
Role:
Thesis CO-Advisor
Created:
2021
Modified:
2025-07-17
Issued:
2025-07-17
วิทยานิพนธ์/Thesis
application/pdf
URL: https://www.lib.ku.ac.th/KUthesis/2564/teepakorn-tos-all.pdf
CallNumber:
TA1637 .T44
eng
DegreeName: Master of Engineering
Level: Master's Degree
Grantor: Kasetsart University
©copyrights Kasetsart University
RightsAccess:
ใช้เวลา
0.026653 วินาที
Teepakorn Tosawadi
| Title | Contributor | Type |
|---|---|---|
| Automatic Rice plant disease evaluation method based on anomaly detection and deep learning
มหาวิทยาลัยเกษตรศาสตร์ Teepakorn Tosawadi | Teerasit Kasetkasem | วิทยานิพนธ์/Thesis |
Teerasit Kasetkasem
Teera Phatrapornnant
| Title | Creator | Type and Date Create |
|---|---|---|
| The SIP-Based radio over internet protocol interoperability communication system for emergency situation
มหาวิทยาลัยเกษตรศาสตร์ Mongkol Raksapatcharawong;Teera phatrapornnant;Yamaoka, Katsunori | Sirinya Tabsombat | วิทยานิพนธ์/Thesis |
Itsuo Kumazawa
| Title | Creator | Type and Date Create |
|---|---|---|
| Land cover mapping classification based on deep-learning
มหาวิทยาลัยเกษตรศาสตร์ Teerasit Kasetkasem;Thitiporn Chanwimaluang;Itsuo Kumazawa;Preesan Rakwatin | Apiwat Lekfuangfu | วิทยานิพนธ์/Thesis |
| Land cover mapping using a random forest classification
มหาวิทยาลัยเกษตรศาสตร์ Teerasit Kasetkasem;Thitiporn Chanwimaluang;Itsuo Kumazawa;Preesan Rakwatin | Panyanat Aonpong | วิทยานิพนธ์/Thesis |
| Text detection and recognition on traffic panel using roadside imagery
มหาวิทยาลัยเกษตรศาสตร์ Somying Thainimit ;Itsuo Kumazawa | Sarwar Khan | วิทยานิพนธ์/Thesis |
| Enhancing classification performance using feature combinations in RGB-D images
มหาวิทยาลัยเกษตรศาสตร์ Ekachai Phaisangittisagul ;Itsuo Kumazawa | Wasif Khan | วิทยานิพนธ์/Thesis |
| Remote sensing image classification using deep convolutional
มหาวิทยาลัยเกษตรศาสตร์ Teerasit Kasetkasem ;Thitiporn Chanwimaluang;Itsuo Kumazawa;Preesan Rakwatin | Watsana Bupphawat | วิทยานิพนธ์/Thesis |