Currently, climate change and human activities are causing rapid deterioration of coral reefs worldwide. Monitoring coral health is essential for marine ecosystem conservation. This project focuses on developing an Artificial Intelligence (AI) model to classify coral health into four categories: Healthy, Bleached, Pale, and Dead using Deep Learning techniques. With pre-trained convolutional neural network (CNN) for image classification. To improve accuracy and mitigate overfitting, 5-fold Cross-Validation is employed during training, and the best-performing model is saved. The results of this project can be applied to monitor coral reef conditions and assist marine scientists in analyzing coral health more efficiently and accurately. This contributes to better conservation planning for marine ecosystems in the future.
ปะการังเป็นองค์ประกอบสำคัญของระบบนิเวศทางทะเล แต่กำลังเผชิญกับภาวะเสื่อมโทรมจากภาวะโลกร้อนและกิจกรรมของมนุษย์ การตรวจสอบสุขภาพของปะการังในปัจจุบันอาศัยการสำรวจภาคสนาม ซึ่งใช้เวลานานและอาจเกิดข้อผิดพลาด โครงการนี้จึงนำเทคโนโลยีปัญญาประดิษฐ์มาใช้ในการวิเคราะห์ภาพถ่ายปะการัง ช่วยให้การจำแนกสุขภาพของปะการังมีความรวดเร็วและแม่นยำยิ่งขึ้น
คณะเทคโนโลยีการเกษตร
This study investigated the effects of seed priming with Chaetomorpha sp. seaweed extract on seed germination and seedling growth of chili pepper. The objective was to examine the influence of seaweed extract concentrations on seed germination and seedling development. Seeds were primed in different concentrations of Chaetomorpha sp. extract, compared with a control treatment. The experiment was conducted using a completely randomized design with four replications. Results showed that seed priming with seaweed extract enhanced seed germination characteristics. Primed seeds exhibited improved germination percentage, germination index, and germination rate compared to the control. Additionally, seedlings from primed seeds showed enhanced root and shoot development. This study demonstrates the potential of Chaetomorpha sp. extract as a promising seed priming agent for improving chili pepper seed quality, which can be applied in the production of high-quality chili pepper seedlings.
คณะบริหารธุรกิจ
CO Breathalyzer with Voice Response is the device to measured the level of CO residual in a person's lung who consume tobacco. Measuring residual CO in human breath can identify the tobacco addiction level instead of measuring nicotine in blood.
คณะแพทยศาสตร์
This study explores the application of deep convolutional neural networks (CNNs) for accurate pill identification, addressing the limitations of traditional human-based methods. Using a dataset of 1,250 images across 10 household remedy drugs, various CNN architectures, including YOLO models, were tested under different conditions. Results showed that natural lighting was optimal for imprinted pills, while a lightbox improved detection for plain pills. The YOLOv5-tiny model demonstrated the best detection accuracy, and efficientNet_b0 achieved the highest classification performance. While the model showed strong results, its generalization is limited by sample size and drug variability. Nonetheless, this approach holds promise for enhancing medication safety and reducing errors in outpatient care.