# Hand Gesture Recognition on ESP32-S3 with ESP-Deep Learning

DevFeed: [Hand Gesture Recognition on ESP32-S3 with ESP-Deep Learning](<https://devfeed.tech/articles/hand-gesture-recognition-on-esp32-s3-with-esp-deep-learning-13881.md>)

Original publisher: [Read original article](<https://developer.espressif.com/blog/hand-gesture-recognition-on-esp32-s3-with-esp-deep-learning/>)

Author: John Lee

Published: 2022-12-02T00:00:00Z

Content type: tutorial

Language: en

Sources: [Blog on Developer Portal](<https://devfeed.tech/sources/blog-on-developer-portal.md>)

Topics: [ESP32-S3](<https://devfeed.tech/topics/esp32-s3.md>), [Deep learning](<https://devfeed.tech/topics/deep-learning.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [ESP-IDF](<https://devfeed.tech/topics/esp-idf.md>), [datasets](<https://devfeed.tech/topics/datasets.md>), [Model Development](<https://devfeed.tech/topics/model-development.md>), [quantization](<https://devfeed.tech/topics/quantization.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [blog](<https://devfeed.tech/tags/blog.md>), [classification](<https://devfeed.tech/tags/classification.md>), [deep-learning](<https://devfeed.tech/tags/deep-learning.md>), [esp-dl](<https://devfeed.tech/tags/esp-dl.md>), [esp-id](<https://devfeed.tech/tags/esp-id.md>), [esp32](<https://devfeed.tech/tags/esp32.md>), [esp32-s3](<https://devfeed.tech/tags/esp32-s3.md>), [espressif](<https://devfeed.tech/tags/espressif.md>), [kaggle](<https://devfeed.tech/tags/kaggle.md>), [quantization](<https://devfeed.tech/tags/quantization.md>)

## AI overview

This tutorial explains how to deploy a deep-learning model for classifying six hand gestures on the ESP32-S3 using Espressif's ESP-DL framework. It covers prerequisites, model development, dataset preparation, train/test/calibration splits, and model quantization.

## Source excerpt

Artificial intelligence transforms the way computers interact with the real world. Decisions are carried by getting data from Tiny low-powered devices and sensors into the cloud. Connectivity, high cost and data privacy are some of the demerits of this method. Edge artificial intelligence is another way to process the data right on the physical device without sending data back and forth improving the latency and security and reducing the bandwidth and power.