Acoustic features (MFSCs and MFCCs) for edge AI
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Updated
Sep 11, 2023 - C
Acoustic features (MFSCs and MFCCs) for edge AI
Sound recognition involving a pre-trained neural network on an embedded STM32 board
Application components for STMicro STM32 MCUs
STM32F429 Online handwritten character classification with Gated Recurrent Unit Neural Network
STM32H7 edge vision: Classical CV + TinyML object counting on-chip, OV2640 camera, FreeRTOS, X-CUBE-AI, PySide6 dashboard
TinyML Use STM32L432KC X-CUBE-AI
Embedded AI hand gesture recognition system featuring FreeRTOS, LVGL, OV2640 and X-CUBE-AI on STM32H743.
STM32F407 edge-AI node for industrial motor predictive maintenance: vibration/sound sensing, on-device anomaly detection (X-CUBE-AI), local alarm, and WiFi data upload.
Recognize handwriting of numbers drawn on the LCD screen
AI Pulse Reconstruction on embedded STM32
Real-time ECG arrhythmia classification on STM32F446RE using a 1-D CNN and ST X-CUBE-AI — trained on MIT-BIH, 98.14% accuracy, 460 KiB flash footprint
AI on microcontroller(MCU) tutorial for inferencing an ImageNet dataset with X-CUBE-AI
Real-time Parkinson's disease tremor detection and severity classification using an MPU9255 accelerometer, STM32F401RE, and an embedded neural network deployed with STM32 X-CUBE-AI.
STM32CubeMX / X-CUBE-AI project running a quantized TTT ResNet on the Nucleo-N657X0-Q NPU.
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