1.Low-Power Processing-in-sensor CMOS Image Sensor 2.Implementation of Low-PowerLow-Latency Deep Learning Chip based on Neuromorphic Intelligence (collaborated with MOST 108-2622-8-007-009) 3.Development of Neuromorphic Chip based on The Fruit Fly VisualSpatial Sensory Systems 4.Hardware-Software Co-Design for Neuromorphic AI Chips

This study proposes a 5G C-V2I (Cellular Vehicle-to-Infrastructure) enabled intelligent trajectory prediction and warning system, which can be implemented in a framework including RSUs (Road Side Units) with radar detection ability and 5G edge computing servers. This study exploits artificial intelligence to predict instant trajectories of vehicles at crossroads. The resulting augmented-awareness navigation information is then broadcasted to road users through 5G C-V2I with low latency. In practical applications, road users can obtain real-time dynamics of surrounding vehicles so that their level of safety can be effectively enhanced.

In agriculture, the team has developed a “Chinese Medicinal Functional Compound Prediction A.I. System” that can predict compounds production during cultivation period. Moreover, in application, we have implemented a smart agricultural platform-AgriTalk to link the “Functional Compound Prediction System”“Smart Fertilization System” to provide a comprehensive management in farm production.

The HeaortaNet is developed by the TW-CVAI team. The HeaortaNet is a deep learning model trained by 70,000 axial images from 200 patients with verified annotations of the pericardiumaorta. It shortens the time for data processing from 60 minutes, by manual segmentation of both pericardiumaorta, to 0.4 seconds. The segmentation accuracy, as assessed by dice similarity coefficient, is 94.8 for the pericardium,91.6 for the aorta. The imaging-based Cardiovascular Risk Prediction module was constructed by analyzing data from the National Health Insurance Databank.

In the context of FinTech, we present Financial Graph Attention Networks (FinGAT) to recommend high-profitable stocks in terms of return ratio using time series of stock pricessector info. Our FinGAT can learn the long-short-term price tendency,model the latent interactionsinfluence between stockssectors without any hand-crafted effort. Experiments conducted on Taiwan Stock, S&P 500,NASDAQ stock markets exhibit remarkable accuracy of FinGAT, comparing to state-of-the-arts (by 11, 14,12 performance improvement). The tech is published in IEEE TKDE 2021.

Through the technique, SamplingPrediction of Lithography Overlay Errors, the costtime of overlay error measurement can be reduced to improve the process efficiency. We identify key sampling through clusteringmachine learning models,design a new sampling algorithm in photolithography process. Due to the complexity of wafermany training factors of wafer data, we combine the clustering algorithm with incremental learning to meet customers＇ unique needsachieve the goal of optimally samplingreducing the costs.

This technology aims to automatically extractdefine features from a data-driven perspective through a series of data engineering, machine learningensemble learning technologies via the big data collected from equipment sensorsquality characteristic measurement results. For products that have no quality measurement, a virtual metrology resultpredicted confidence score are provided as a decision-making basis for process control.

PCA-BM includes two models: “Automatic BMs Segmentation AI Model”" Distant Brain Failure Prediction Model". The former one uses C2FNAS (coarse to fine network architecture search) to detect the location, size,number of brain metastases. The latter uses radiomics to extract numerous radiographic featuresemploys machine learning methods such as XGBoost to establish a prognostic model of brain metastases. PCA-BM provides more precision treatment decisions for patientsimproves personalizedaccurate overall stereotactic radiosurgery planning.

The technology is video-based blood pressure monitoring which will help people know the continuous BP status in real time. Also, the contactless measurement can make a daily health record. We have conducted clinical trials in hospitalsestablished a large database to optimize AI solution. The system joins the physicians＇ specialty to analyze the users＇ health status with AI,takes care of human life with technology.