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Semantic MediaWiki
There are 1 incomplete or pending task to finish installation of Semantic MediaWiki. An administrator or user with sufficient rights can complete it. This should be done before adding new data to avoid inconsistencies.- AI:AI licences
- AI:Artificial Intelligence overview
- AI:Capture an Image Dataset with STM32
- AI:Datalogging guidelines for a successful NanoEdge AI project
- AI:Deep Quantized Neural Network support
- AI:FP-AI-FACEREC1 getting started
- AI:FP-AI-MONITOR1 an introduction to the technology behind
- AI:FP-AI-MONITOR1 getting started
- AI:FP-AI-MONITOR1 how to implement Acoustic Scene Classification
- AI:FP-AI-MONITOR1 how to integrate a different AI Model for Human Activity Recognition (HAR)
- AI:FP-AI-MONITOR1 user manual
- AI:FP-AI-MONITOR2 getting started
- AI:FP-AI-MONITOR2 user manual
- AI:FP-AI-NANOEDG1 V1.0 getting started
- AI:FP-AI-NANOEDG1 V2.0 getting started
- AI:FP-AI-NANOEDG1 V2.0 user manual
- AI:Getting started with FP-AI-VISION1
- AI:Getting started with STM32Cube.AI Developer Cloud
- AI:How to Build an Anomaly Detection Project for Predictive Maintenance with NanoEdge AI Studio
- AI:How to add AI model to OpenMV ecosystem
- AI:How to allocate more Flash memory to the Cortex M7 of the STM32H747 Discovery board
- AI:How to automatize code generation and validation with X-CUBE-AI CLI
- AI:How to collect data
- AI:How to correct fisheye distortion on STM32
- AI:How to create Arduino Rock-Paper-Scissors game using NanoEdge AI Studio
- AI:How to create a current sensing classifier using NanoEdge AI Studio
- AI:How to create a dual-tone multi-frequency classifier using NanoEdge AI Studio
- AI:How to create a multi-state vibrations classifier using NanoEdge AI studio
- AI:How to create a multi-state vibrations classifier using NanoEdge AI studio (using STEVAL-MKBOXPRO)
- AI:How to detect collisions in a washing machine with vibrations
- AI:How to install STM32 model zoo
- AI:How to install X-CUBE-AI through STM32CubeMX
- AI:How to measure machine learning model power consumption with STM32Cube.AI generated application
- AI:How to perform Human Activity Recognition using FP-AI-MONITOR1
- AI:How to perform anomaly detection using FP-AI-MONITOR1
- AI:How to perform condition monitoring on STM32
- AI:How to perform motion sensing on STM32L4 IoTnode
- AI:How to perform people counting using FP-AI-VISION1 and STM32H747XI
- AI:How to run larger models on STM32H747I-DISCO
- AI:How to split the weights
- AI:How to upgrade a STM32 project with a new version of the X-CUBE-AI
- AI:How to use STM32Cube.AI command line
- AI:How to use Teachable Machine to create an image classification application on STM32
- AI:How to use a quantized model with OpenMV and Cube.AI
- AI:How to use transfer learning to perform image classification on STM32
- AI:Introduction to Artificial Intelligence with STM32
- AI:Memory placements on STM32 with STM32Cube.AI
- AI:NEAI Utils.png
- AI:NanoEdgeAI Library for 1-class classification (1CC)
- AI:NanoEdgeAI Library for extrapolation (E)
- AI:NanoEdge AI Anomaly Detection library for ISPU
- AI:NanoEdge AI Emulator for 1-class classification (1CC)
- AI:NanoEdge AI Emulator for anomaly detection (AD)
- AI:NanoEdge AI Emulator for classification (CL)
- AI:NanoEdge AI Emulator for extrapolation (E)
- AI:NanoEdge AI Emulator for n-class classification (nCC)
- AI:NanoEdge AI Library for 1-class classification (1CC)
- AI:NanoEdge AI Library for anomaly detection (AD)
- AI:NanoEdge AI Library for classification (CL)
- AI:NanoEdge AI Library for extrapolation (E)
- AI:NanoEdge AI Library for n-class classification (nCC)
- AI:NanoEdge AI Studio
- AI:NanoEdge AI Studio: CLI
- AI:ONNX
- AI:STM32Cube.AI model benchmark (backup)
- AI:STM32Cube.AI model performances
- AI:TVM Benchmarking
- AI:X-CUBE-AI Command Line Interface
- AI:X-CUBE-AI Quick Start Guide
- AI:X-CUBE-AI documentation
- AI:X-CUBE-AI support of ONNX and TensorFlow quantized models
- AI:X-LINUX-AI getting started
