CakeResume Talent Search

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De 4 a 6 años
6-10 años
10-15 años
Más de 15 años
Taipei, Taiwan
Avatar of Winter Wu.
Avatar of Winter Wu.
行政人員 @誠品總公司
2016 ~ 2016
品牌行銷
Más de un año
合作及交流想法。 技能 電腦文書 Word Power Point Excel 簡報製作 繪圖 Adobe llustrator Adobe Photoshop 健身 中華民國健身指導員C級 RTS Thump Boxing 學歷 樹人醫療專科學校, 其他, 物理治療系, 2019 ~ 2022 取得考物理治療師的資格 中國文化大學, 學士學位, 廣告系行銷組, 2015 ~ 2020 學習廣告的行銷企劃
word
powerpoint
excel
A tiempo completo / Interesado en trabajar a distancia
6-10 años
樹人醫療專科學
物理治療系
Avatar of 張巍瀛.
Avatar of 張巍瀛.
Past
系統分析師 @ATM Electronic
2015 ~ 2018
專案企劃;專案經理;後端工程師;系統分析師
En un plazo de tres meses
系統分析師, Jun 2019 ~ Feb平台需求及規格文件撰寫。 2. 釐清需求檢核邏輯以及流程細節。 3. 協調所需時程,並依用戶提供之資料設計功能。 4. 系統功能驗證測試,與用戶驗收與再調整之協調溝通 5. 系統操作問題排除與排查系統產生邏輯 ATM
MSSQL
VS Code
Sublime Text
Desempleado
A tiempo completo / Interesado en trabajar a distancia
6-10 años
東吳大學
資訊科學

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Problem-Solving
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En seis meses
Sr. software engineer (Full Remote) @ Gatos Vision
Gatos Vision
2022 ~ Presente
Taiwan
Professional Background
Situación actual
Empleado
Progreso en la búsqueda de empleo
Professions
Software Engineer, Research / R&D, Machine Learning Engineer
Fields of Employment
Manufacturing, Inteligencia Artificial / Aprendizaje Automático, Software
Experiencia laboral
1-2 años
Management
Ninguno
Habilidades
Python
C++
Tensorflow (Keras)
OpenCV
Revit
Deep Learning
Artificial Intelligence
mechine learning
Computer Vision
Halcon
Idiomas
Chinese
Nativo o bilingüe
English
Intermedio
Japanese
Principiante
Job search preferences
Posición
機器學習、資料科學工程師
Tipo de trabajo
A tiempo completo
Ubicación
Taiwan, 台灣, Taipei, 台灣
A distancia
Interesado en trabajar a distancia
Freelance
Sí, soy un autónomo amateur.
Educación
Escuela
National Taiwan University
Mayor
Civil Engineering
Imprimir
W8pta5tkps8w1p7ljk0l

Zhao-Yang Zhuang (莊昭陽)

Experience with computer vision, deep learning. I am very passionate about design a novel DL model architecture for real world problems and hope to participate in more types of applications.

ML engineer  Data scientist

  [email protected]       https://www.linkedin.com/in/rogan-zhuang/

  https://github.com/ZhuangRogan

Educations

National Taiwan University

Civil Engineering, Computer-Aided Engineering Group (M.S. degree)

(2018 ~ 2020)

Master Thesis: 

Deep-learning method assisted crane for sway prediction: Recurrent Kalman Network.

University@2x

Work Experiences

(Automation Services Co., LTD.)  (AI/CV Engineer)

(Feb, 2021 - Oct, 2021)
  • The main developer of AI/CV algorithm.
  • Compiled the AI/CV part of automatic fabric inspection machine alone from scratch.

Research Experiences

Deep-learning method assisted crane for sway prediction : Recurrent Kalman Network   

(Dec, 2019 - Jun, 2020)

Robotic LAB, NTU & 祐彬 Construction Co., Ltd

  • Predicting the future position of a payload by RKN to assist in the automation of crane.
  • The state of the payload system can be inferred by the combined information between the image pixels.
Key achievement: Assists the automation of the crane in a new way, and does not require any physical parameters but only image data of the payload. RKN, the new time-series forecasting architecture will be 10x better than LSTM.

Tensorflow(Keras) OpenCV Python C/C++  Deep Learning 

The second generation of automatic fabric inspection machine 

 (Feb, 2021 - Apr, 2021)

Automation Services Co., LTD.

  • Detecting the defects on the textile by deep learning that efficiency is at least ten times of manual visual inspection.
  • Calculate the area and location of defects by semantic segmentation.
  • The prototype machine can detect the width of about two meters with eight cameras.

 C# Deep Learning

The third generation of automatic fabric inspection machine 

 (May, 2021 - Oct, 2021)

Automation Services Co., LTD.

  • Based on the second-generation inspection machine, all of the features are upgraded, such as image grabbing system, camera calibration system, deep learning framework, thread optimization, etc.
  • This mass production machine is online.
  • Not implemented using Tensorflow or Pytorch.

Key achievement: 100% detection of defects required by customers, 36x8 frames per second detection speed.

C# Deep Learning Cameras System Multithread Programming

Side Projects

  • Image automatic labeling: CNN-base object tracking by Siam-Net. [labeling 90x faster than manual]
  • Document layout analyzing: locate file elements (titles, text, pictures, etc.) by image segmentation. 
  • HousePrice-prediction: Predict the HousePrice in Feature Engineering & Advanced Regression. [Kaggle top 0.04%]
  • Flowers classification: Distributed training a CNN to classify 104 kinds of flower pictures. [Kaggle top 0.09%]
Resume
Perfil
W8pta5tkps8w1p7ljk0l

Zhao-Yang Zhuang (莊昭陽)

Experience with computer vision, deep learning. I am very passionate about design a novel DL model architecture for real world problems and hope to participate in more types of applications.

ML engineer  Data scientist

  [email protected]       https://www.linkedin.com/in/rogan-zhuang/

  https://github.com/ZhuangRogan

Educations

National Taiwan University

Civil Engineering, Computer-Aided Engineering Group (M.S. degree)

(2018 ~ 2020)

Master Thesis: 

Deep-learning method assisted crane for sway prediction: Recurrent Kalman Network.

University@2x

Work Experiences

(Automation Services Co., LTD.)  (AI/CV Engineer)

(Feb, 2021 - Oct, 2021)
  • The main developer of AI/CV algorithm.
  • Compiled the AI/CV part of automatic fabric inspection machine alone from scratch.

Research Experiences

Deep-learning method assisted crane for sway prediction : Recurrent Kalman Network   

(Dec, 2019 - Jun, 2020)

Robotic LAB, NTU & 祐彬 Construction Co., Ltd

  • Predicting the future position of a payload by RKN to assist in the automation of crane.
  • The state of the payload system can be inferred by the combined information between the image pixels.
Key achievement: Assists the automation of the crane in a new way, and does not require any physical parameters but only image data of the payload. RKN, the new time-series forecasting architecture will be 10x better than LSTM.

Tensorflow(Keras) OpenCV Python C/C++  Deep Learning 

The second generation of automatic fabric inspection machine 

 (Feb, 2021 - Apr, 2021)

Automation Services Co., LTD.

  • Detecting the defects on the textile by deep learning that efficiency is at least ten times of manual visual inspection.
  • Calculate the area and location of defects by semantic segmentation.
  • The prototype machine can detect the width of about two meters with eight cameras.

 C# Deep Learning

The third generation of automatic fabric inspection machine 

 (May, 2021 - Oct, 2021)

Automation Services Co., LTD.

  • Based on the second-generation inspection machine, all of the features are upgraded, such as image grabbing system, camera calibration system, deep learning framework, thread optimization, etc.
  • This mass production machine is online.
  • Not implemented using Tensorflow or Pytorch.

Key achievement: 100% detection of defects required by customers, 36x8 frames per second detection speed.

C# Deep Learning Cameras System Multithread Programming

Side Projects

  • Image automatic labeling: CNN-base object tracking by Siam-Net. [labeling 90x faster than manual]
  • Document layout analyzing: locate file elements (titles, text, pictures, etc.) by image segmentation. 
  • HousePrice-prediction: Predict the HousePrice in Feature Engineering & Advanced Regression. [Kaggle top 0.04%]
  • Flowers classification: Distributed training a CNN to classify 104 kinds of flower pictures. [Kaggle top 0.09%]