Chien-Chou Lin

Professor, Department of Computer Science and Information Engineering

Laboratory

Chuan-Yu Chang

President, National Yunlin University of Science and Technology
Distinguished Professor, Department of Computer Science and Information Engineering
Director, Intelligent Recognition Industry Service Research Center (YunTech IRIS Center)

Laboratory

Medical Image Processing Laboratory

Research Topics

Digital Processing, Facial Spots and Pigments, New Crying Sound and Nerves, Machine Learning/neural Learning, Medical Image Processing, Automated Optical Inspection (AOI), Neural Networks Image, Nerve Detection, Computer Inspection Vision

Experience

President, National Yunlin University of Science and Technology (2025/02-now)

Chief Digital Officer, Service Systems Technology Center, ITRI (2023/08-2025/01)

Deputy Chief Executive Officer, Service Systems Technology Center, ITRI (2020/08-2023/07)

President, Chinese Image Processing and Pattern Recognition Society (2020/10-2022/11)

Chief Technology Officer, Service Systems Technology Center, ITRI (2019/08-2020/07)

Director, IRIS Research Center, YunTech (2018/01-now)

President, Taiwan Association for Web Intelligence Consortium (2017/10-2021/11)

Distinguished Professor, Department of Computer Science and Information Engineering, YunTech (2013/08-now)

Dean, Office of Research and Development, YunTech (2011/08-2019/07)

Director, Incubation Center for Academia-Industry Collaboration and Intellectual Property, YunTech (2011/08-2019/07)

Chair, Department of Computer Science and Information Engineering, YunTech (2009/08-2011/07)

Chung-Wen Hung

Professor, Department of Electrical Engineering

Laboratory

Advanced Purpose Integrated Circuits and Systems Design Laboratory

Deng-Chuan Cai

Distinguished Professor, Department of Industrial Design
Vice Dean, College of Design
Dean, Graduate School of Design-Doctoral Program

Bang-Ning Hwang

Professor, Department of Business Administration

Yung-Kuan Tseng

Professor, Department of Cultural Heritage Conservation

Arthur, Chang

Assistant Professor, Department of Information Management

Chung-Chian Hsu

Distinguished Professor, Department of Information Management

Laboratory

Department Personal Page

Shr-Chang Shia

Distinguished Professor, Department of Electronic Engineering

Laboratory

Department Personal Page

Ming-Hwa Sheu

Distinguished Professor, Department of Electronic Engineering

Laboratory

Department Personal Page

Chian C. Ho

Associate Professor, Department of Electrical Engineering
Section Director, YunTech Office of Research and Development- Employment and Alumni Liaison Group

Laboratory

Embedded System on Chip Laboratory

Hsien-Huang P. Wu

Distinguished Professor, Department of Electrical Engineering
Director, Intelligent and Monitoring Research Center
Director, Power Electronics and Sustainable Energy Technology R & D Center

Laboratory

Automated optical inspection and measurement laboratory

Ching-Lung Chang

Distinguished Professor, Department of Computer Science and Information Engineering

Laboratory

Embedded Network System Laboratory

Wen-Fong Wang

Associate Professor, Department of Computer Science and Information Engineering

Laboratory

E-Health Informatics & System Laboratory

Yi-Lung Lin

Associate Professor, Department of Computer Science and Information Engineering

Szu-Hong Wang

Assistant Professor, Department of Electronic Engineering

Dun-Wei Cheng

Assistant Professor, Department of Computer Science and Information Engineering

Chao-Yang Lee

Assistant Professor, Department of Computer Science and Information Engineering

Ching-Lung Su

Associate Professor, Department of Electronic Engineering
Section Director, Library-System Information Group

Laboratory

Department Personal Page


Name of Technology	Character Recognition and Defect Detection of Metal
Developer of Technology	Department of Computer Science and Information Engineering Yi-Lung Lin, Associate Professor
Summary of Technology	Casting Since the metal surface is easy to reflect light, it is not easy to identify using traditional optical character detection. This technology is used to identify the characters of several English/number symbols on the control valve. The symbols include numbers 0 to 9 and English letters A to Z. The technology that has been used includes image preprocessing, deep convolution layer, time series layer, and connectionist temporal classification layer. Considering the field application, it is designed as a lightweight model running on the mobile phone, and a set of character optical detection systems that integrate computer vision. This technology reduces the identification time and improves the accuracy of identification, which is convenient for subsequent application in product inventory management and production history filing after production is completed. Technical characteristic: 1. Digital management of products traceability 2. Reducing the working hours for field personnel to input data 3. Increasing the efficiency of the assembly and shipping process 4. Improving the production history system


Name of Technology	Application of Hyperspectral Smart Agriculture in Food Safety Taking Eggs as Examples
Developer of Technology	Department of Computer Science and Information Engineering Shih-Yu Chen, Associate Professor
Summary of Technology	This technology uses Snapshot to take a hyperspectral image of egg defects and uses a line scan camera to take a picture of egg freshness. The obtained hyperspectral image is processed and trained using an AI depth learning algorithm. In terms of prediction speed, this technology can achieve real-time identification (3.23 ms/image), and the overall accuracy of the two classifications can reach more than 95%. Technical characteristic: 1. Non-invasive: Using the non-invasive hyperspectral camera 2. Real-time: Conducting real-time analysis by AI depth learning algorithm. Accuracy can reach more than 95% and the prediction time of one image only takes 3.23ms. 3. Economize manpower: Saving the manpower of traditional manual sections. 4. Increase production: Long-running


Name of Technology	AI-based Textile Defect Inspection
Developer of Technology	Department of Computer Science and Information Engineering Chien-Chou Lin, Professor
Summary of Technology	Generative adversarial network model is first built and defect identification/location network is used to find the location of defects. The degree of automation of textile defect detection technology is significantly upgraded. An algorithm is designed to improve the accuracy of identification. The defects are located in the images and the corresponding locations of the textile and defects are recorded in real time for later examination and review. This technique is also useful in ensuring the areas of textile with defects are avoided during the cutting process. An identification accuracy of higher than 95% is achieved.


Name of Technology	Industry 4.0 Connected Intelligent Ball Screw
Developer of Technology	Department of Computer Science and Information Engineering Ching-Lung Chang, Professor
Summary of Technology	The performance of ball screws can be effectively monitored by integrating the hybrid sensor for vibration and temperature with algorithm. The user is able to monitor the condition of each work station in real time on remote web pages. Based on the results, timely maintenance can be arranged to avoid unexpected shutdown. Other benefits include high equipment availability and energy efficiency. Intelligent ball screw diagnosis: Vibration alert – Warning signals are triggered as abnormal vibration occurs in order to ensure the normal operation of the ball screws. The incident records are logged as well. Lifetime pre-diagnosis – The online pre-diagnosis enables ball screw health monitoring, facilitates maintenance arrangement and avoids emergency shutdown. Intelligent lubrication – The automatic lubrication ensures worker safety and avoids shutdown of ball screws caused by insufficient lubrication. This condition-based lubrication approach is cost effective and environmentally friendly.


Name of Technology	Agricultural Land Survey Aiot Application and Vehicle Integrated System
Developer of Technology	Bachelor Program in Interdisciplinary Studies Wang Szu-Hong, Project-Appointed Assistant Professor


Name of Technology	Vehicle Surround View Display System with Free Viewing Function (AVM)
Developer of Technology	Department of Electronic Engineering Ching-Lung Su, Associate Professor
Summary of Technology	4 optical wide-angle fisheye lenses are used to provide a panoramic view of the vehicle, showing high-resolution images of the entire vehicle from above and at any angle of view. When parking and reversing, obstacles around the vehicle can be inspected without blind spot, improving safety and protection.


Name of Technology	Indoors Gait Positioning System (Indoors GPS)
Developer of Technology	Department of Computer Science and Information Engineering Wen-Fong Wang, Associate Professor
Summary of Technology	The indoors GPS applies the cell-phone built-in sensors (accelerometer, magnetometer, gyroscope, etc.) with dead reckoning algorithms to locate users, who stay in a complex indoors separated space. This novel idea has been developed in a cell-phone user APP. This app has the functions of service initialization, indoor navigation, check-in, and more.


Name of Technology	Mowing robot
Developer of Technology	Department of Computer Science and Information Engineering Ching-Lung Chang, Professor
Summary of Technology	Embedded platform, combined with RTK-GPS, 9-axis sensor and the Kalman filter, PID control, ultrasonic sensing, image recognition and other technologies. Create a mowing robot with precise autonomous mowing and obstacle avoidance capability. Relevant technologies can be transferred to achieve automatic mowing and save manpower. It can be applied to lawn finishing in campus, parks, homes, etc.
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Name of Technology	Intelligent Trash Can Featuring Patrolling and Surveillance
Developer of Technology	Department of Electrical Engineering Chian-C. Ho, Associate Professor
Summary of Technology	Traditional trash cans are usually installed in the out-of-the-way dead corners so that people are often littering the trash anywhere because of urgency or inconvenience. This work “Intelligent Trash Can Featuring Patrolling and Surveillance” can collect the trach proactively from people so as to improve the effectiveness and efficiency of cleaning service. On the other hand, traditional security surveillance cameras are usually installed on the ceiling corners or crossways so that there are still many dead spaces and security loopholes to be monitored. This work can patrol and inspect proactively so as to improve the effectiveness and efficiency of surveillance service.


Name of Technology	Big Data Analysis and Abnormal Equipment Real-Time Detection and Diagnosis
Developer of Technology	Department of Information Management Chung-Chian Hsu, Distinguished Professor
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Name of Technology	Community Health Care and Fitness Tracking and Service System
Developer of Technology	Department of Computer Science and Information Engineering Wen-Fong Wang, Associate Professor
Summary of Technology	The system is capable of monitoring multiple heath data, evaluate and record the health status of the elderly and provide the user with all of the relevant information regarding the elderly through a mobile app.


Name of Technology	Drunk Driving Sensing System based on Heartbeat Micro – Quiver Sensing Technology
Developer of Technology	Department of Computer Science and Information Engineering Wen-Fong Wang, Associate Professor
Summary of Technology	The system can measure the heartbeat vibrations by setting it on the steering wheel or other places that are in direct contact with the body, or it can be applied to personal 3C items such as smart bracelets. This technology can be installed on the steering wheel or seat in car, with the alarm system and cloud database, it can immediately detect whether the driver is drinking or not, and prevent this kind of behavior or notify affected members to the scene to deal with it.


Name of Technology	A Tracking and Locating System for Seniors With Dementia
Developer of Technology	Department of Computer Science and Information Engineering Wen-Fong Wang, Associate Professor
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Name of Technology	Cultural Relics and Artwork Intelligent Recognition Design
Developer of Technology	Department of Cultural Heritage Conservation Yung-Kuan Tseng, Professor
Summary of Technology	Use intelligent recognition technology to develop unique identification tools for antiquities or artworks created by specific artists or painters. Boosting cultural development is based on a sound cultural and artwork market, and the security of transactions depends on authenticity – fake recognition, preserve truly valuable antiquities.
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Name of Technology	Visual and LiDAR Synchronous Positioning and Mapping Technology
Developer of Technology	Department of Electrical Engineering Chian-C. Ho, Associate Professor
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Name of Technology	IOT Application that Implement Automatic Photography with Sound Recognition
Developer of Technology	Department of Electronic Engineering Ming-Hwa Sheu, Distinguished Professor
Summary of Technology	Detecting and recognizing the sound of clinking glasses during “Cheers! “, it will automatically activate the camera and take a picture from the sound source, these photos will be uploaded to the voice control device named ” IOT Application that Implement Automatic Photography with Sound Recognition”, the simple and handy design allows various parties such as wedding venues and bars to receive the most natural and vivid gathering photos.
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Name of Technology	Gait Analysis System with Intelligent Image Recognition
Developer of Technology	Department of Computer Science and Information Engineering Wen-Fong Wang, Associate Professor
Summary of Technology	This technology can accurately record and analyse the human gait and be applied to neurology to nervous system inspection.
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Name of Technology	Interactive Ice Hockey Game Control
Developer of Technology	Department of Computer Science and Information Engineering Ching-Lung Chang, Professor
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Name of Technology	Automotive Electronics – Applying Structured Light for Free Space Detection
Developer of Technology	Department of Electronic Engineering Shr-Chang Shia, Distinguished Professor


Name of Technology	Using Hyperspectral Technology to Estimate Vase Life of Anthurium Cut
Developer of Technology	Department of Computer Science and Information Engineering Shih-Yu Chen, Associate Professor
Summary of Technology	The use of hyperspectral information with multi-band and non-interaction characteristics combined with machine learning methods to estimate the vase life of anthurium and accurately predict the aging time of anthurium to increase market value.
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Name of Technology	Smart Product Grading and Defect Screening Peanuts
Developer of Technology	Department of Computer Science and Information Engineering Shih-Yu Chen, Associate Professor
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Name of Technology	Smart New Agriculture Real-time Automated Hyperspectral Defect Detection System
Developer of Technology	Department of Computer Science and Information Engineering Shih-Yu Chen, Associate Professor
Summary of Technology	After using the snapshot-type hyperspectral camera to obtain the image of coffee beans, the recognition accuracy can be greatly improved through the band selection and AI deep learning technology, and the automatic integration with the robot arm can accurately and instantly screen the defective coffee beans It turns out that this technology is not only a fast, comprehensive and non-invasive detection method, it can improve coffee quality and reduce a lot of labor costs. This technology can be applied to the screening of defects in various agricultural products, such as coffee, peanuts, and nuts.
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Name of Technology	Efflorescence Detection on The Surface of The Tunnel
Developer of Technology	Department of Computer Science and Information Engineering Chien-Chou Lin, Professor
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Name of Technology	Extreme 3D Modeling and Recognition Technology
Developer of Technology	IRIS research center Director Department of Computer Science and Information Engineering Chuan-Yu Chang, Distinguished Professor
Summary of Technology	The technology comprises of advanced optical zoom, face tracking as well as 3D face biometric technology and can be applied to 3D face recognition, cosmetic surgery and orthodontics.
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Name of Technology	Learning Observation System
Developer of Technology	IRIS Research Center Director Department of Computer Science and Information Engineering Chuan-Yu Chang, Distinguished Professor
Summary of Technology	The “learning observation system” developed by IRIS center Professor Chuanyu-Chang‘s team is to capture the learner’s face and movements and analyze the expression information (including happy, sad, and expressionless) and specific actions (Including raising left hand, raising right hand, raising hands and getting down), assist teachers to understand the emotional changes of students in class and student’s reaction, can find the students that need to be paid attention to, and adjust teaching methods or communication effectively in real time. In addition, it can also detect “violent behavior” in the team, or use other “people flow detection” technologies to prevent people from entering dangerous areas or leaving the team.
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Name of Technology	Infant Crying Translator
Developer of Technology	Director, IRIS Research Center Department of Computer Science and Information Engineering Chuan-Yu Chang, Distinguished Professor
Summary of Technology	Before learning how to express the emotions or physiological/psychological requirements with language, infants usually express how they feel to parents through crying. We have collected more than 2,000,000 infant cries. Machine learning and the big data analysis techniques are used to automatically adapt the crying model for each infant. The cloud system is built to collect and analyze the cries. Infant Crying Translator recognizes four types of infant crying, including being hungry, in pain, wet-diaper and sleepy. Experimental results have revealed good performance of the proposed system, the recognition accuracy is up to 92%, 85.4%, 83.8%, and 77% for infants born within 2 weeks, 1 month, 2 months, and 4 months, respectively.
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Name of Technology	Non-contact Bio-signals Measuring Technologies
Developer of Technology	Director, IRIS Research Center Department of Computer Science and Information Engineering Chuan-Yu Chang, Distinguished Professor
Summary of Technology	Heart rate and respiration rate are vital signs checked for accessing the health condition of a patient. Traditionally, heart rate and respiration rate are measured with non-continuous, contact-based approaches. Using AI and computer vision technologies, our research team has successfully developed a “non-contact” bio-signals measuring technology based on “temperature change” and “blood color change”. This technology facilitates real-time, accurate and continuous measurement of heart rate and respiration rate. The error rates of measurement are ±4 beats/minute and ±1 breaths/minute, respectively, for heart rate and respiration rate. “Temperature change” Object sensing technology is employed to identify the position of a human face. The temperatures are taken at the forehead, face mask and nose areas and the heart rate and respiration rate are calculated based on the temperature change. The “body temperature, heart rate and respiration rate” can be measured at the same time by using thermal cameras only. The approach is feasible as well even if the patient is wearing a face mask. “Blood color change” The heart rate and respiration rate of a patient are estimated based on the color change of the cells on the face caused by blood flow. This lightweight application has low hardware requirement and can be implemented with low-end laptop or Raspberry Pi development board. High performance is still achieved at a low cost!


Name of Technology	Thyroid Image Diagnosis Technology
Developer of Technology	Director, IRIS Research Center Department of Computer Science and Information Engineering Chuan-Yu Chang, Distinguished Professor
Summary of Technology	This technology assists doctors during clinical diagnosis to reduce the difficulty in diagnosis, decrease the inspection time and improve the diagnosis rate. The contributions are as follows: (1) Realization of automatic thyroid gland segmentation in various medical images (2) Segmentation and classification of thyroid nodules in ultrasound images (3) Volume estimation of the thyroid gland in ultrasound images (4) Segmentation of thyroid tumors and (5) automatic detection of the Graves disease in the thyroid gland


Name of Technology	A Platform for the Construction of Shoe Last Point Cloud Models
Developer of Technology	Department of Computer Science and Information Engineering Chien-Chou Lin, Professor
Summary of Technology	The technology uses a mobile platform with a line laser scanner to obtain the shoe last’s point cloud data from all angles. The point cloud data are merged using point cloud merging algorithms to obtain the complete shoe last’s point cloud model.


Name of Technology	AI Monitoring System for Safe Behavior of Entrance/Exit on Production Line
Developer of Technology	Director, IRIS Research Center Department of Computer Science and Information Engineering Chuan-Yu Chang, Distinguished Professor
Summary of Technology	Technology content: Important issue of industrial safety accident prevention, to avoid the employees who do not follow the safety procedures and seek the convenience to cause industrial safety incidents. Therefore, a set of AI Monitoring System for Safe Behavior of Entrances/Exits on Production Line was developed, using pedestrian tracking and behavior recognition technology to timely monitor whether employees follow safety standards and improve the safety of employees’ operations.


Name of Technology	Tire Bubble Detection Technology Based on Incremental YOLO
Developer of Technology	Director, IRIS Research Center Department of Computer Science and Information Engineering Chuan-Yu Chang, Distinguished Professor
Summary of Technology	Although digital shearography can show subtle defects that cannot be observed with the naked eye, it is still up to the site personnel to determine whether it is a defect, and the judgment standards may vary due to different experiences. Our team proposed the incremental YOLO architecture to greatly increase the detection rate. The bubble defect detection rate is about 98%, and it only takes 0.076 seconds to judge a single image. The detection speed is very fast, which can help companies achieve semi-automatic detection processes and greatly reduce detection human resources.


Name of Technology	Point Cloud Object Recognition and Tracking Algorithm
Developer of Technology	Department of Computer Science and Information Engineering Chien-Chou Lin, Professor
Summary of Technology	Laser light’s visual ability are stronger than image, it won’t affected by light illumination, and won’t misjudged shadow as an object, this technology can identify the type of object , such as cars or pedestrians, it can also track 360 degree moving objects.
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Name of Technology	Automatic Drug Identification System
Developer of Technology	Department of Electrical Engineering, Hsien-Huang P. Wu, Distinguished Professor
Summary of Technology	Combining computer vision with Raspberry pi, and using relays to control the two cameras to take pictures of the front and back of the tablet, it can automatically identify the name and the number of pills, and reduce the mistakes made by health care worker when taking pills and supplement, because the pills are too similar, avoid causing patients to ingest the wrong medicine.


Name of Technology	Automatic Inspection Technology for Golf Surface Defects
Developer of Technology	Department of Electrical Engineering Hsien-Huang P. Wu, Distinguished Professor
Summary of Technology	The inspector will proceed the inspection over the uneven and non-flat surface of a golf ball to detect several types of surface defects – for example, dents, burs and scratch which damages the surface. For a given 11 types of various defect, the detection rate is about 97% and speed of the inspection is about 23 balls per minute.


Name of Technology	Automatic Defect Detection Of Wood Board
Developer of Technology	Department of Electrical Engineering Hsien-Huang P. Wu, Distinguished Professor
Summary of Technology	The system is based on computer stereo vision, Which uses the triangulation method to detect the defect by a line laser and an industrial camera. Putting the wood board on a mobile platform for movement and a line of laser is projected onto the surface of the board, the depth image of the board surface can then be reconstructed to 1mm accuracy. The depth image can be used for defect detection by simple image processing, and the defects detected are used for performing subsequent glue filling operation or cutting operation.


Name of Technology	Shoe Surface 3D Reconstruction and Path Planning for Glue Spraying
Developer of Technology	Department of Electrical Engineering Hsien-Huang P. Wu, Distinguished Professor
Summary of Technology	The technology combines computer vision with the laser triangulation technology to build a 3D scanning system, which generates automatic glue spraying path information according to the computations and analysis performed by the algorithm. The information is transmitted to a six-axial robotic arm, shoe-surface glue-spraying system to automate and standardize the glue spraying process. The technology automates the glue-spraying path modelling to increase the efficiency by 80% and enables the possibility of small-scale production of multiple products.


Name of Technology	Automatic Measurement and Inspection of Electronic
Developer of Technology	Department of Electrical Engineering, Hsien-Huang P. Wu, Distinguished Professor
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Name of Technology	Copper Foil Defect Detection
Developer of Technology	Department of Electrical Engineering, Hsien-Huang P. Wu, Distinguished Professor
Summary of Technology	Traditional AOI is able to inspect 23 types of defects. Using feature descriptors, classification is difficult and time-consuming. To solve this problem we introduce AI deep learning to perform direct classification. Preliminary research result shows that the accuracy in defect classification is 93%, which continues to improve with the availability of more data. This technology can replace existing inspection equipment (11 stages) and reduce the cost of the original equipment by 50%.


Name of Technology	3D Visual Identification and Orientation Estimation of Large Objects
Developer of Technology	Department of Electrical Engineering Hsien-Huang P. Wu, Distinguished Professor
Summary of Technology	Using an inexpensive 3D depth camera, the system can capture the depth information of the scene. The depth information is used to construct the surface geometry of the 3D object and perform feature extraction. The feature extraction can be matched to the existing 3D CAD model to identify the classification and calculate the position and orientation angle of the object. These three types of information can finally be transferred back to the 6-axis robot for automatic pick-and-place action.


Name of Technology	The Trajectory Generation and Offset Correction of The Spraying Path of The Intelligent Racket
Developer of Technology	Department of Electrical Engineering Hsien-Huang P. Wu, Distinguished Professor
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Name of Technology	Image Pre-Processing for Tire Defect Detection — Image Calibration Based on the Fusion of Depth and Color Images
Developer of Technology	Department of Computer Science and Information Engineering Chien-Chou Lin, Professor
Summary of Technology	The technology integrates a laser displacement meter and a high-speed color camera. The tire surface’s depth variation is captured by a laser displacement meter and combined with the tire surface’s visual images captured by a colour camera. The two types of information are rectified and fused to obtain the texture characteristics from the images and the physical attributes from the depth images to improve the accuracy of tire defect detection.


Name of Technology	Design and Development of International Disease Classification Code ICD-10 Coding System
Developer of Technology	Bachelor Program in Interdisciplinary Studies Jung-Sheng Chang, Project-appointed Assistant Professor
Summary of Technology	Use big data analysis technology to help encode the doctor’s diagnosis of medical information into ICD-10 to improve the accuracy and speed of coding and reduce costs. Develop an out-patient clinic intelligent medical pre-diagnosis system that allows patients to answer questions in advance through mobile phones or multi-media interactive machines before the consultation, assist doctors to conduct more in-depth consultations during limited visits time to improve medical quality.


Name of Technology	Light Fingerprint Identification System on Edge Computing
Developer of Technology	Department of Electrical Engineering Chung-Wen Hung, Professor
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Chang Hsuan-Ting

Professor, Department of Electrical Engineering

Shih-Yu Chen

Associate Professor, Department of Computer Science and Information Engineering

Laboratory

Hyperspectral Signal and Image Processing Laboratory

First Prize

Best Innovation Award

Third Prize


Name of Technology	Apply Deep Learning to Inspect Solder Joints in DRAM Modules
Developer of Technology	Director, IRIS Research Center Department of Computer Science and Information Engineering Chuan-Yu Chang, Distinguished Professor
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Name of Technology	Zero Contact Detection Facial-Heart Rate and Stroke Detection System
Developer of Technology	Director, IRIS Research Center Department of Computer Science and Information Engineering Chuan-Yu Chang, Distinguished Professor
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Name of Technology	Smart Baby Monitor
Developer of Technology	Director, IRIS Research Center Department of Computer Science and Information Engineering Chuan-Yu Chang, Distinguished Professor
Summary of Technology	Obstruction of the nose and mouth by vomit or quilts is the main cause of sudden infant death. Different baby sleeping postures will increase the difficulty of face detection. Therefore, a deep learning neural network is adopted to detect baby faces and a novel algorithm is proposed to detect vomiting of infants. The proposed method can detect baby’s face effectively under the complex background and various illumination conditions. The system can help parents monitor the baby whether his/her mouth and nose is covered with vomit or quilt. The system can real-time notification to parents, to improve infant safety and reduce the burden on parents.


Name of Technology	Early Gastric Endoscopic Lesion Detection
Developer of Technology	Department of Electrical Engineering Chang Hsuan-Ting, Professor
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Name of Technology	Artificial Intelligence Automatically Detects and Segmentation of Pneumothorax Symptoms in Chest Radiographs in Real Time
Developer of Technology	Department of Electrical Engineering Chian-C. Ho, Associate Professor
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Name of Technology	Medical Imaging Endotracheal Tube Detection
Developer of Technology	Department of Information Management Chung-Chian Hsu, Distinguished Professor
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Name of Technology	Lung Mass Detectionfrom Chest X-Ray Image
Developer of Technology	Director, IRIS Research Center Department of Computer Science and Information Engineering Chuan-Yu Chang, Distinguished Professor
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Name of Technology	Chamfering Tool Diagnosis System
Developer of Technology	Department of Electrical Engineering Chung-Wen Hung, Associate Professor
Summary of Technology	It is currently used in the diagnosis of chamfering tools. In the future, by reading the processing signals of different machines, and retraining the model that meets the application from the collected data, then detect the abnormality. Achieve the same anomaly detection effect, improve the overall efficiency and yield of the production line.


Name of Technology	Light Fingerprint Identification System on Edge Computing
Developer of Technology	Department of Electrical Engineering Chung-Wen Hung, Associate Professor
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