AI academic exchange with the Taiwan-India Artificial Intelligence Overseas Research Center of Chung Cheng University, and the team of Professor Pao-Ann Hsiung demonstrated AI-related technologies, including smart epidemic prevention systems (thermal image body temperature sensing, face recognition), intelligent people and luggage transaction sensing, and smart security monitoring system, intelligent flow analysis system, etc.
No. 123, Section 3, University Road, Douliu City, Yunlin County (3F-AI304/AI305,Dream Hub Building)
Professor, Department of Electrical Engineering
Advanced Purpose Integrated Circuits and Systems Design Laboratory
Distinguished Professor, Department of Industrial Design
Vice Dean, College of Design
Dean, Graduate School of Design-Doctoral Program
Professor, Department of Business Administration
Professor, Department of Cultural Heritage Conservation
Assistant Professor, Department of Information Management
Distinguished Professor, Department of Information Management
Distinguished Professor, Department of Electronic Engineering
Distinguished Professor, Department of Electronic Engineering
Associate Professor, Department of Electrical Engineering
Section Director, YunTech Office of Research and Development- Employment and Alumni Liaison Group
Distinguished Professor, Department of Electrical Engineering
Director, Intelligent and Monitoring Research Center
Director, Power Electronics and Sustainable Energy Technology R & D Center
Distinguished Professor, Department of Computer Science and Information Engineering
Associate Professor, Department of Computer Science and Information Engineering
Associate Professor, Department of Computer Science and Information Engineering
Distinguished Professor, Department of Computer Science and Information Engineering
Director, IRIS Research Center
Chief Digital Officer, Service Systems Technology Center, ITRI
Medical Image Processing Laboratory
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
President, Chinese Image Processing and Pattern Recognition Society (2020/11-2022/11)
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)
Assistant Professor, Department of Electronic Engineering
Assistant Professor, Department of Computer Science and Information Engineering
Data and Knowledge Engineering Laboratory
Assistant Professor, Department of Computer Science and Information Engineering
Associate Professor, Department of Electronic Engineering
Section Director, Library-System Information Group
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| Name of Technology | Character Recognition and Defect Detection of Metal |
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| 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 |
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| Name of Technology | Application of Hyperspectral Smart Agriculture in Food Safety Taking Eggs as Examples |
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| 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: |
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| Name of Technology | AI-based Textile Defect Inspection |
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| 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. |
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| Name of Technology | Industry 4.0 Connected Intelligent Ball Screw |
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| 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: |
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| Name of Technology | Agricultural Land Survey Aiot Application and Vehicle Integrated System |
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| Developer of Technology | Bachelor Program in Interdisciplinary Studies Wang Szu-Hong, Project-Appointed Assistant Professor |
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| Name of Technology | Vehicle Surround View Display System with Free Viewing Function (AVM) |
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| 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. |
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| Name of Technology | Indoors Gait Positioning System (Indoors GPS) |
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| 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. |
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| Name of Technology | Mowing robot |
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| 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 |
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| 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. |
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| Name of Technology | Big Data Analysis and Abnormal Equipment Real-Time Detection and Diagnosis |
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| 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 |
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| 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. |
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| Name of Technology | Drunk Driving Sensing System based on Heartbeat Micro – Quiver Sensing Technology |
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| 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. |
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| Name of Technology | A Tracking and Locating System for Seniors With Dementia |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| Developer of Technology | Department of Electronic Engineering Shr-Chang Shia, Distinguished Professor |
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| Name of Technology | Using Hyperspectral Technology to Estimate Vase Life of Anthurium Cut |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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” “Blood color change” |
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| Name of Technology | Thyroid Image Diagnosis Technology |
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| 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 |
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| Name of Technology | A Platform for the Construction of Shoe Last Point Cloud Models |
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| 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. |
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| Name of Technology | AI Monitoring System for Safe Behavior of Entrance/Exit on Production Line |
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| 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. |
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| Name of Technology | Tire Bubble Detection Technology Based on Incremental YOLO |
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| 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. |
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| Name of Technology | Point Cloud Object Recognition and Tracking Algorithm |
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| 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 |
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| 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. |
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| Name of Technology | Automatic Inspection Technology for Golf Surface Defects |
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| 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. |
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| Name of Technology | Automatic Defect Detection Of Wood Board |
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| 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. |
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| Name of Technology | Shoe Surface 3D Reconstruction and Path Planning for Glue Spraying |
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| 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. |
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| Name of Technology | Automatic Measurement and Inspection of Electronic |
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| Developer of Technology | Department of Electrical Engineering, Hsien-Huang P. Wu, Distinguished Professor |
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| Name of Technology | Copper Foil Defect Detection |
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| 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%. |
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| Name of Technology | 3D Visual Identification and Orientation Estimation of Large Objects |
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| 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. |
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| Name of Technology | The Trajectory Generation and Offset Correction of The Spraying Path of The Intelligent Racket |
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| 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 |
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| 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. |
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| Name of Technology | Design and Development of International Disease Classification Code ICD-10 Coding System |
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| 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. |
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| Name of Technology | Light Fingerprint Identification System on Edge Computing |
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| Developer of Technology | Department of Electrical Engineering Chung-Wen Hung, Professor |
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Professor, Department of Electrical Engineering
Associate Professor, Department of Computer Science and Information Engineering
Associate Professor, Department of Computer Science and Information Engineering
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| Name of Technology | Apply Deep Learning to Inspect Solder Joints in DRAM Modules |
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| 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 |
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| 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 |
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| 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. |
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| Name of Technology | Early Gastric Endoscopic Lesion Detection |
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| 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 |
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| Developer of Technology | Department of Electrical Engineering Chian-C. Ho, Associate Professor |
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| Name of Technology | Medical Imaging Endotracheal Tube Detection |
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| 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 |
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| 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 |
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| 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. |
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| Name of Technology | Light Fingerprint Identification System on Edge Computing |
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| Developer of Technology | Department of Electrical Engineering Chung-Wen Hung, Associate Professor |
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Professor, Department of Creative Life Design
Project-Appointed Assistant Professor, Bachelor Program in Interdisciplinary Studies
Assistant Professor, Department of Architecture and Interior Design
Associate Professor, Department of Applied Foreign Languages
Associate Professor, Department of Computer Science and Information Engineering
