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没有符合的项目。
4 到 6 年
6 到 10 年
10 到 15 年
15 年以上
Software engineer
Algorithm Research & Development @適着三維科技股份有限公司 TG3D Studio Inc.2021 ~ 现在
・
Software Engineer
一個月內
Patrick Hsu AI Research & Development As a seasoned AI engineer with six years of experience, I specialize in computer vision, 3D body model reconstruction, generative AI, and possessing some knowledge in natural language processing (NLP). | New Taipei City, [email protected] Work Experience (6 years) Algorithm Research & Design• TG3D Studio MayPresent A skilled engineer specialized in computer vision and generative AI with experience in developing and training AI models for digital fashion applications. Body AI: Virtual Try On Integrated cutting-edge technologies such as Stable Diffusion, ControlNet, and Prompt Engineering to create a sophisticated system for
就职中
・
正在积极求职中
全职 / 对远端工作有兴趣
4 到 6 年
國立台灣大學
・
生物產業機電工程所最轻量、快速的招募方案，数百家企业的选择
搜寻简历，主动联系求职者，提升招募效率。
- 浏览所有搜寻结果
- 每日可无限次数开启陌生对话
- 搜尋僅開放付費企業檢視的简历
- 检视使用者信箱 & 电话
搜寻技巧
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Search a precise keyword combination
senior backend php
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Use quotes to search for an exact phrase
"business development"
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Use the minus sign to eliminate results containing certain words
UI designer -UX
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。
变通能力
遇到突发事件能冷静应对，并随时调整专案、客户、技术的相对优先序。
沟通能力
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。
团队合作能力
具有向心力与团队责任感，愿意倾听他人意见并主动沟通协调。
领导力
专注于团队发展，有效引领团队采取行动，达成共同目标。
专业背景
目前状态
就学中
求职阶段
专业
软体工程师, Python 开发人员, 机器学习工程师
产业
软件, 人工智能 / 机器学习, 机器人科学
工作年资
小於 1 年
管理经历
无
技能
语言能力
English
・
专业
German
・
进阶
Chinese
・
母语或双语
求职偏好
希望获得的职位
Software Engineer
预期工作模式
全职
期望的工作地点
台灣台北市, 台灣新北市, 台灣新竹市新竹, 台灣桃園
远端工作意愿
对远端工作有兴趣
接案服务
否
学历
学校
國立清華大學
主修科系
資訊應用研究所
林佳縈 Chia Ying Lin
Computer Vision Reseacher
Computer Vision Lab, NTHU
With 4-year solid training in computer science fundamentals, 2-year independent research experience in computer vision, and diverse hands-on development experiences, I always pursue excellence, crave new challenges, and am open to all possibilities.
https://github.com/lykasbongbongbong
Skills
Languages
- Python (familiar)
- C++, C
- JAVA
Deep Learning Frameworks
- PyTorch (familiar)
- Tensorflow
CV & DL Libraries
- OpenCV
- Keras
Development Tools
- Git/Github
- RESTFul APIs
Web Development
- HTML, CSS, JS
- Python Flask
- PHP, Laravel
- MySQL, NoSQL(mongoDB)
- AWS
Others
- English TOEFL iBT 97
- English TOEIC 935
- German B2
Education
Master's Studies, Computer Vision Lab, NTHU
Dept. Information Systems and Application, Sep 2020~Now
- Anomaly detection and segmentation for smart manufacturing as primary research target
Bachelor Degree, WASN Lab, NCU
Dept. Computer Science, Sep 2016 ~ June 2020
Exchange Student, Hochschule München, Germany
Dept. Informatik (Computer Science), Sep 2019 ~ Feb 2020
Experiences
August 2021
Attendee,
Machine Learning Summer School, NTU
August 2021
Backend Developer (Anomaly Detection Demo Website),
CVLab, FUTEX 2021
- Use Python Flask, MySQL for RestFul APIs development
- Optimized backend system with Python threading to support sudden massive traffic
June 2018 ~ July 2019, 1y1m
Full-Stack Web Developer (NCU Internship Web)
Career Center NCU
- Reconstruct website with Laravel Framework
- Optimize backend and database to handle larger amounts of access
- Over 30% of users received intern opportunities via this site
- Website Link: https://ncuinternship.careercenter.ncu.edu.tw/
Master Thesis:
SABDN: Self-Attention Based Deviation Network for few-shot anomaly detection and segmentation (Under Review ECCV 2022)
Contributions
- Combine self-attention mechanism with feature extraction CNN network and anomaly synthesis mechanism for anomaly scoring to achieve outstanding anomaly detection accuracy under few-shot setting
- Reach SOTA performance on benchmark dataset MVTecAD dataset and BTAD dataset with over 90 percent reduction in training data requirements
Side Projects
GlueGAN: a generative model based on SuperGlue structure
- Extend MagicLeap’s SuperGlue end-to-end GNN concept for object synthesis to solve synthetic object image generation problem
- 10% accuracy improvement compared to initial GAN backbone
Let's play GAN with flows and friends!
- Generate synthetic object images with multi-label conditions with conditional GAN manner
- Human faces generation by conditional normalizing flow
2048: by Temporal Difference Learning Approach (RL)
- Construct TD-learning algorithm and design own n-tuple network to solve 2048 game
- Reach 98% 2048-tile win rate in 1000 games
The LunarLander: under Deep Q-Network and DDPG manner (RL)
- Implement DQN and DDPG network to solve LunarLander game problem
- Thoroughly understand Deep Q-learning, actor-critic mechanism
Real-Time car detection and counting system
- Retrain YOLOv3 with our own hatchback dataset
- Reach average accuracy: 99% on both day-light and evening scenarios
林佳縈 Chia Ying Lin
Computer Vision Reseacher
Computer Vision Lab, NTHU
With 4-year solid training in computer science fundamentals, 2-year independent research experience in computer vision, and diverse hands-on development experiences, I always pursue excellence, crave new challenges, and am open to all possibilities.
https://github.com/lykasbongbongbong
Skills
Languages
- Python (familiar)
- C++, C
- JAVA
Deep Learning Frameworks
- PyTorch (familiar)
- Tensorflow
CV & DL Libraries
- OpenCV
- Keras
Development Tools
- Git/Github
- RESTFul APIs
Web Development
- HTML, CSS, JS
- Python Flask
- PHP, Laravel
- MySQL, NoSQL(mongoDB)
- AWS
Others
- English TOEFL iBT 97
- English TOEIC 935
- German B2
Education
Master's Studies, Computer Vision Lab, NTHU
Dept. Information Systems and Application, Sep 2020~Now
- Anomaly detection and segmentation for smart manufacturing as primary research target
Bachelor Degree, WASN Lab, NCU
Dept. Computer Science, Sep 2016 ~ June 2020
Exchange Student, Hochschule München, Germany
Dept. Informatik (Computer Science), Sep 2019 ~ Feb 2020
Experiences
August 2021
Attendee,
Machine Learning Summer School, NTU
August 2021
Backend Developer (Anomaly Detection Demo Website),
CVLab, FUTEX 2021
- Use Python Flask, MySQL for RestFul APIs development
- Optimized backend system with Python threading to support sudden massive traffic
June 2018 ~ July 2019, 1y1m
Full-Stack Web Developer (NCU Internship Web)
Career Center NCU
- Reconstruct website with Laravel Framework
- Optimize backend and database to handle larger amounts of access
- Over 30% of users received intern opportunities via this site
- Website Link: https://ncuinternship.careercenter.ncu.edu.tw/
Master Thesis:
SABDN: Self-Attention Based Deviation Network for few-shot anomaly detection and segmentation (Under Review ECCV 2022)
Contributions
- Combine self-attention mechanism with feature extraction CNN network and anomaly synthesis mechanism for anomaly scoring to achieve outstanding anomaly detection accuracy under few-shot setting
- Reach SOTA performance on benchmark dataset MVTecAD dataset and BTAD dataset with over 90 percent reduction in training data requirements
Side Projects
GlueGAN: a generative model based on SuperGlue structure
- Extend MagicLeap’s SuperGlue end-to-end GNN concept for object synthesis to solve synthetic object image generation problem
- 10% accuracy improvement compared to initial GAN backbone
Let's play GAN with flows and friends!
- Generate synthetic object images with multi-label conditions with conditional GAN manner
- Human faces generation by conditional normalizing flow
2048: by Temporal Difference Learning Approach (RL)
- Construct TD-learning algorithm and design own n-tuple network to solve 2048 game
- Reach 98% 2048-tile win rate in 1000 games
The LunarLander: under Deep Q-Network and DDPG manner (RL)
- Implement DQN and DDPG network to solve LunarLander game problem
- Thoroughly understand Deep Q-learning, actor-critic mechanism
Real-Time car detection and counting system
- Retrain YOLOv3 with our own hatchback dataset
- Reach average accuracy: 99% on both day-light and evening scenarios