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进阶搜寻
On
4 到 6 年
6 到 10 年
10 到 15 年
15 年以上
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
超過一年
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
全职 / 对远端工作有兴趣
6 到 10 年
樹人醫療專科學
物理治療系
Avatar of 張巍瀛.
Avatar of 張巍瀛.
曾任
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
三個月內
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
待业中
全职 / 对远端工作有兴趣
6 到 10 年
東吳大學
資訊科學

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职场能力评价定义

专业技能
该领域中具备哪些专业能力(例如熟悉 SEO 操作,且会使用相关工具)。
问题解决能力
能洞察、分析问题,并拟定方案有效解决问题。
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有效传达个人想法,且愿意倾听他人意见并给予反馈。
时间管理能力
了解工作项目的优先顺序,有效运用时间,准时完成工作内容。
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半年內
Sr. software engineer (Full Remote) @ Gatos Vision
Gatos Vision
2022 ~ 现在
Taiwan
专业背景
目前状态
就职中
求职阶段
专业
软体工程师, 研发, 机器学习工程师
产业
制造, 人工智能 / 机器学习, 软件
工作年资
1 到 2 年
管理经历
技能
Python
C++
Tensorflow (Keras)
OpenCV
Revit
Deep Learning
Artificial Intelligence
mechine learning
Computer Vision
Halcon
语言能力
Chinese
母语或双语
English
中阶
Japanese
初阶
求职偏好
希望获得的职位
機器學習、資料科學工程師
预期工作模式
全职
期望的工作地点
Taiwan, 台灣, Taipei, 台灣
远端工作意愿
对远端工作有兴趣
接案服务
是,我利用业余时间接案
学历
学校
National Taiwan University
主修科系
Civil Engineering
列印
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%]
简历
个人档案
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%]