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M

manayang

GitHub @ManaEstras ↗

Machine Learning Engineer

公司
—
位置
Shenzhen
Stars
3
粉丝 / 仓库
31

代表作品 / 项目

  • EECS222-UCI-EmbeddedSystem⭐ 2This project conducts a case study System-level modeling and design to model a special application on System-on-Chip. The overall project goal is to design a suitable embedded system model of this application and describe it in a System-Level Description Language (SLDL). This embedded specification model will then not only be simulated for functional and timing validation, but also be refined for synthesis and implementation as an embedded System-on-Chip (SoC) suitable for use in a digital camera. This article explains the details throughout this case study of Canny Edge Detection, including the basic of Canny application, creating a stimulatable model in SLDL, creating structural hierarchy, pipelining, parallelization, performance estimation and optimization. As the outcomes of each steps of modeling recorded, the general procedure of System-level modeling and design and developing new methodologies of System-on-Chip is also presented. A well-defined methodology like the one presented in this article will help product planning divisions to quickly develop new products or to derive completely new business models
  • SensorSolution17⭐ 1The project aims to develop a wearable device to detect the exposure to the Ultraviolet and polluted air of the people who wears this device, and to alarm them when they have been exposed to dangerous amount of UV or air pollution. Besides, through wireless communication, the device can transmit data to smartphones, PCs or Cloud platforms, where data can be organized and analyzed.
  • autoresearch⭐ 0Claude Autoresearch Skill — Autonomous goal-directed iteration for Claude Code. Inspired by Karpathy's autoresearch. Modify → Verify → Keep/Discard → Repeat forever.
  • HunyuanOCR⭐ 0HunyuanOCR-1.5: Making Lightweight OCR VLMs Faster and Better
  • transformers⭐ 0🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
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