EdgeAI Lab with Microcontrollers Session #1: Overview of EdgeAI Applications
📌 Session #1: Overview of EdgeAI Applications
📌 Brief introduction of different hardware and a short talk about the pipelines in edgeAI applications.
About :
MLT Edge AI Lab was formed in 2020 when a team of researchers/engineers visited a local farm in Chiba to brainstorm solutions for problems faced by local farmers. EdgeAI Lab was formed with an aim of creating an OPEN environment where anyone can experiment with tools and apply their learnings to create quick prototypes.
MLT EdgeAI Lab with Microcontrollers Weekly Series is created by Naveen Kumar and Yoovraj Shinde, to learn and share about the steps in building EdgeAI applications. We will take a look at the general steps in EdgeAI pipeline and the different hardware available to deploy the models. We will also take a look at 2 simple applications, to strengthen our understanding of data collection/ processing/building/deployment and inference.
We are looking forward to active participation from the MLT community members to build cool apps together. We will do a short brainstorming session in the end to find good ideas which we can work together throughout the series.
📌 Session Leads: Naveen Kumar & Yoovraj Shinde
📌 ORGANIZER BIO
Naveen Kumar is a Senior Technical Scientist at RIKEN working on microbial DNA sequencing data analysis. He is a maker, tinkerer, embedded electronics hobbyist, and Edge AI enthusiast. In his free time, he enjoys watching movies, photography, and playing with microcontrollers.
https://www.hackster.io/naveenbskumar
Yoovraj Shinde is a software engineer/manager in the research department at Rakuten Institute of Technology, Tokyo. His background is in electronics engineering and loves to tinker around with circuits/hardware/robots for kids. He is interested in working around Machine Learning and Hardware and learning new things. / yoovraj-shinde
● FULL CURRICULUM
📌 Session #1: Overview of EdgeAI Applications
📌 Session #2: Motion-Based Application using IMU
📌 Session #3: Audio Based Application using Microphone
📌 Session #4: Wrap-up session
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