Hello, I'm Wayne, graduated from the National Taichung University of Science and Technology. I have worked in Nayna Technology before and is responsible for web development, docker deployment, data training of the neural network.
Backend Engineer, Software Engineer
[email protected]
.Net Framework / .Net Core
Laravel (php)
Flask (python)
jQuery
bootstrap
css
javascript
LAMP
Docker
ESXI
Object detection(YOLO,SSD)
object classification(VGG16, ResNet50)
•Design EPAS Report System(.Net Framework) and help log the machine issues in it to generate the real-time report.
•Deploy docker environment(tensorflow+flask+nfs).
•Build the neural networks(VGG16/ResNet50) to classify needle mark images.
•Use C Language/GPIB to communicate between Advantest Tester and TEL Prober.
• Build Linux machines in ESXi and JSP Projects to each VM Machine.
• Refactor the codes of the JSP project using Laravel.
• Build and Maintain LAMP.
• Develop and Maintain Android App.
09/2017 - 02/2020
Professor: Da-Ren Chen
Master Thesis: On the Study of Road Quality Inspections Using Deep Learning Methods
Explore the effect of pixel difference(PD) on neural networks, and propose a framework of Roadcrack Detector (RD) to recognize the road crack.
RD is composed of Gaussian Mixture Model(GMM) splitting datasets and neural network training, In the first step of GMM part, use Gaussian Mixture Method(GMM) cluster images, In the second step, try to use YOLO/SSD to find out the crack of road.
• Develop an Android app to collect the RSSI signal from IBeacon, and save data to CSV.
• Use Fingerprint to train the CSV data by Decision Tree and predict the User position when the app get the user signal.
Hello, I'm Wayne, graduated from the National Taichung University of Science and Technology. I have worked in Nayna Technology before and is responsible for web development, docker deployment, data training of the neural network.
Backend Engineer, Software Engineer
[email protected]
.Net Framework / .Net Core
Laravel (php)
Flask (python)
jQuery
bootstrap
css
javascript
LAMP
Docker
ESXI
Object detection(YOLO,SSD)
object classification(VGG16, ResNet50)
•Design EPAS Report System(.Net Framework) and help log the machine issues in it to generate the real-time report.
•Deploy docker environment(tensorflow+flask+nfs).
•Build the neural networks(VGG16/ResNet50) to classify needle mark images.
•Use C Language/GPIB to communicate between Advantest Tester and TEL Prober.
• Build Linux machines in ESXi and JSP Projects to each VM Machine.
• Refactor the codes of the JSP project using Laravel.
• Build and Maintain LAMP.
• Develop and Maintain Android App.
09/2017 - 02/2020
Professor: Da-Ren Chen
Master Thesis: On the Study of Road Quality Inspections Using Deep Learning Methods
Explore the effect of pixel difference(PD) on neural networks, and propose a framework of Roadcrack Detector (RD) to recognize the road crack.
RD is composed of Gaussian Mixture Model(GMM) splitting datasets and neural network training, In the first step of GMM part, use Gaussian Mixture Method(GMM) cluster images, In the second step, try to use YOLO/SSD to find out the crack of road.
• Develop an Android app to collect the RSSI signal from IBeacon, and save data to CSV.
• Use Fingerprint to train the CSV data by Decision Tree and predict the User position when the app get the user signal.