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
คณะวิศวกรรมศาสตร์
The Thai Sign Language Generation System aims to create a comprehensive 3D modeling and animation platform that translates Thai sentences into dynamic and accurate representations of Thai Sign Language (TSL) gestures. This project enhances communication for the Thai deaf community by leveraging a landmark-based approach using a Vector Quantized Variational Autoencoder (VQVAE) and a Large Language Model (LLM) for sign language generation. The system first trains a VQVAE encoder using landmark data extracted from sign videos, allowing it to learn compact latent representations of TSL gestures. These encoded representations are then used to generate additional landmark-based sign sequences, effectively expanding the training dataset using the BigSign ThaiPBS dataset. Once the dataset is augmented, an LLM is trained to output accurate landmark sequences from Thai text inputs, which are then used to animate a 3D model in Blender, ensuring fluid and natural TSL gestures. The project is implemented using Python, incorporating MediaPipe for landmark extraction, OpenCV for real-time image processing, and Blender’s Python API for 3D animation. By integrating AI, VQVAE-based encoding, and LLM-driven landmark generation, this system aspires to bridge the communication gap between written Thai text and expressive TSL gestures, providing the Thai deaf community with an interactive, real-time sign language animation platform.
วิทยาเขตชุมพรเขตรอุดมศักดิ์
Traditional Thong Yip dessert, or locally known as Khee Man dessert, is a dessert made from flour made from yellow rice.
คณะเทคโนโลยีการเกษตร
This experiment aimed to study the suitable types of polymers for coating with chlorophyll extract and the quality of cucumber seeds after coating. The experiment was planned using a Completely Randomized Design (CRD) with four replications, consisting of five methods involving seeds coated with different types of polymers: Polyvinylpyrrolidone, Sodium Alginate, Carboxy Methyl Cellulose, and Hydroxypropyl Methylcellulose, each polymer being coated alongside chlorophyll, with uncoated seeds serving as the control method. The coating substance was prepared by extracting chlorophyll from mango leaves, then mixed with each type of polymer at a concentration of 1%, using an 8% concentration of chlorophyll extract. The properties of each coating method, such as pH and viscosity of the coating substance, were examined before coating the cucumber seeds with a rotary disk coater model RRC150 at a coating rate of 1,100 milliliters per 1 kilogram of seeds. Subsequently, the seeds were dried to reach the initial moisture level using a hot air blower, and seed quality was assessed in various aspects, including seed moisture, germination rate under laboratory conditions, germination index, and seed fluorescence under a portable ultraviolet light illuminator, as well as light emission spectrum analysis using a Spectrophotometer. The experiment found that each type of polymer could be used to form a film together with chlorophyll, which had appropriate pH and viscosity for the coating without affecting seed quality and showed fluorescence on the seed surface both under portable ultraviolet light and spectral emission analysis with a Spectrophotometer. Using HPMC as the film-forming agent with chlorophyll was the most suitable method, enhancing seed fluorescence efficiency.