The 2022 TWS AIHPC Technology Forum series, led by experts from TWCC, will guide you through understanding the advantages and importance of TWCC's high-speed AIHPC computing performance for AI deep learning!
With the advancement of technology, more and more 3C products are accompanying our lives, bringing convenience but also increasing the usage time of 3C products, which in turn affects people's vision and other related health problems. Many eye diseases involve abnormal lesions of the microvessels in the eye.
In November, we will demonstrate how U-Net's image segmentation technology in smart healthcare applications can extract microvascular images of the eye to assist doctors in conducting highly specialized, detailed, and irregular medical examinations. These cases often have the characteristic of scarce data. U-Net can effectively and accurately predict the image edges, which helps to significantly reduce doctors' examination time and labor costs.
Furthermore, in competitions like the Airbus Ship Detection Challenge on Kaggle, which automatically locates ships in satellite imagery, U-Net, using a convolutional network architecture, achieved high-performance and accurate results. It is also widely used in fields such as environmental engineering and geographic exploration, enabling more effective and accurate image segmentation data on limited datasets.
| Date: November 30, 2022 (Wednesday)
| Time: 15:00-16:30
| Target audience: Information managers, IT and technology managers, development teams, engineers, and corporate executives, as well as anyone interested in U-Net image segmentation applications.
You will learn:
- U-Net image segmentation was performed using the TensorFlow framework via TWCC CCS.
Organizer: Taiwan Smart Cloud
Co-organizers: Taiwan Cloud & IoT Industry Association, Artificial Intelligence Technology Foundation