Algorithm Research & Development @適着三維科技股份有限公司 TG3D Studio Inc.
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2021 ~ Present
Software Engineer
Within one month
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
Business Development / Product Manager / Product Marketing/ Strategy Manager
Within one month
Jimmy Lu (呂正彥) Senior Product Manager [Consumer Electronics Expatriate PM/Sales/BD] Entrepreneurship business development & management Leadership flexible & efficient international/cross-functional organizing Target-oriented project lead & SOP consolidation, product lifecycle management Begin with the end in mind Go-to-market execution Taipei, Taiwan < > London, UK https://www.linkedin.com/in/itsjimmy/ [email protected] Work experience Senior Product Manager [Consumer NB & Gaming ] • ASUSTeK Computer Indonesia JulDec 2023 | Jakarta, Indonesia Key responsibilities & Achievements - #business management #business development #team leading #cross-functional organizing
Business Development Project Management
Cross-Functional Project Management
Product Life Cycle Management
Unemployed
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Ready to interview
Full-time / Interested in working remotely
4-6 years
國立陽明交通大學(National Yang Ming Chiao Tung University)
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Bachelor of management , Management of Transportation and Logistics
本論文由非幾何法之統計模型出發,考慮隨機到達時間模型 (Random Arrival Time Model),修正原有非幾何法統計模型之假設,讓本論文更適合用於實際之車間通訊環境。最後透過現有之實務量測結果,將本論文模型與非幾何法統計模型做比較,結果顯示本論文模型確實更接近實務量測之結果,驗證本論文之模型比以往之非幾何法統計模型更適合用於車間通訊。
本論文由非幾何法之統計模型出發,考慮隨機到達時間模型 (Random Arrival Time Model),修正原有非幾何法統計模型之假設,讓本論文更適合用於實際之車間通訊環境。最後透過現有之實務量測結果,將本論文模型與非幾何法統計模型做比較,結果顯示本論文模型確實更接近實務量測之結果,驗證本論文之模型比以往之非幾何法統計模型更適合用於車間通訊。