This project has been developed to address medical challenges related to the process of counting and classifying blood cells from samples, a task that requires both time and high precision. To reduce the workload of medical personnel, the developers have created a platform and an artificial intelligence (AI) system capable of automatically classifying and counting cells from sample images. This system is designed to assist medical laboratory technicians by enabling them to work more efficiently and accurately, reducing the time required for analysis. Furthermore, it promotes the advancement of medical technology, ensuring effective usability from classrooms and laboratories to hospitals.
เนื่องจากคณะผู้จัดทำมีโอกาสได้พูดคุยกับบุคลากรที่ทำงานในสายอาชีพเทคนิคการแพทย์ จึงเล็งเห็นถึงปัญหาด้านระยะเวลาการทำงาน โดยเฉพาะในกระบวนการแยกและนับจำนวนเซลล์เม็ดเลือด ซึ่งเป็นขั้นตอนที่ใช้เวลาค่อนข้างมาก คณะผู้จัดทำจึงเล็งเห็นโอกาสในการนำความรู้ที่มีมาพัฒนาแนวทางใหม่เพื่อช่วยลดภาระงานของบุคลากรทางการแพทย์ หากสามารถลดระยะเวลาในกระบวนการดังกล่าวได้ ด้วยเหตุนี้เอง โครงการนี้จึงถูกริเริ่มขึ้นมา โดยมีเป้าหมายเพื่อพัฒนาเทคโนโลยีที่สามารถสนับสนุนการทำงานของบุคลากรทางการแพทย์ และยกระดับคุณภาพของกระบวนการตรวจวินิจฉัยให้มีความรวดเร็วและแม่นยำยิ่งขึ้น
คณะเทคโนโลยีสารสนเทศ
This research presents a deep learning method for generating automatic captions from the segmentation of car part damage. It analyzes car images using a Unified Framework to accurately and quickly identify and describe the damage. The development is based on the research "GRiT: A Generative Region-to-text Transformer for Object Understanding," which has been adapted for car image analysis. The improvement aims to make the model generate precise descriptions for different areas of the car, from damaged parts to identifying various components. The researchers focuses on developing deep learning techniques for automatic caption generation and damage segmentation in car damage analysis. The aim is to enable precise identification and description of damages on vehicles, there by increasing speed and reducing the work load of experts in damage assessment. Traditionally, damage assessment relies solely on expert evaluations, which are costly and time-consuming. To address this issue, we propose utilizing data generation for training, automatic caption creation, and damage segmentation using an integrated framework. The researchers created a new dataset from CarDD, which is specifically designed for cardamage detection. This dataset includes labeled damages on vehicles, and the researchers have used it to feed into models for segmenting car parts and accurately labeling each part and damage category. Preliminary results from the model demonstrate its capability in automatic caption generation and damage segmentation for car damage analysis to be satisfactory. With these results, the model serves as an essential foundation for future development. This advancement aims not only to enhance performance in damage segmentation and caption generation but also to improve the model’s adaptability to a diversity of damages occurring on various surfaces and parts of vehicles. This will allow the system to be applied more broadly to different vehicle types and conditions of damage inthe future
คณะเทคโนโลยีการเกษตร
-
คณะวิศวกรรมศาสตร์
The project uses artificial intelligence (AI) and deep learning to develop a smart police system (Smart Police) to analyze the identity of individuals and vehicles suspected of involvement in crimes. The system uses CCTV cameras to detect people with concealed weapons and track vehicles involved in crimes. The system also sends alerts to the police when a crime is detected. The Smart Police system is a collaboration between the Faculty of Engineering, King Mongkut's Institute of Technology Ladkrabang, the Provincial Police Region 2, the Chachoengsao Foundation for Development, and the Smart City Office of Chachoengsao Province. The system is designed to prevent and deter crime, increase public safety and order, and build a network of cooperation between the government, the private sector, and the community. The system is currently under development, but it has the potential to be a valuable tool for law enforcement. The system could help to reduce crime and improve public safety in Chachoengsao Province and other parts of Thailand.