Label Inspection - Create impulse

Shebin Jose Jacob / Label Inspection Public

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An impulse takes raw data, uses signal processing to extract features, and then uses a learning block to classify new data.

Description	Recommended
Images Officially Supported Processes discrete images for object detection or classification.
Time series data Officially Supported Operates on time series sensor data like vibration or audio data. Lets you slice up data into windows.

Did you know? You can bring your own DSP code.

Description	Author	Recommended
Image Officially Supported Preprocess and normalize image data, and optionally reduce the color depth.	Edge Impulse
Image Officially Supported Preprocess and normalize image data, and optionally reduce the color depth.	Edge Impulse
Flatten Officially Supported Flatten an axis into a single value, useful for slow-moving averages like temperature data, in combination with other blocks.	Edge Impulse
Audio (MFCC) Officially Supported Extracts features from audio signals using Mel Frequency Cepstral Coefficients, great for human voice.	Edge Impulse
Audio (MFE) Officially Supported Extracts a spectrogram from audio signals using Mel-filterbank energy features, great for non-voice audio.	Edge Impulse
Spectral Analysis Officially Supported Great for analyzing repetitive motion, such as data from accelerometers. Extracts the frequency and power characteristics of a signal over time.	Edge Impulse
Spectrogram Officially Supported Extracts a spectrogram from audio or sensor data, great for non-voice audio or data with continuous frequencies.	Edge Impulse
Audio (Syntiant) Officially Supported Syntiant only. Compute log Mel-filterbank energy features from an audio signal.	Syntiant
IMU (Syntiant) Officially Supported Syntiant only. Great for analyzing repetitive motion, such as data from accelerometers. Extracts the frequency and power characteristics of a signal over time.	Syntiant
Raw Data Officially Supported Use data without pre-processing. Useful if you want to use deep learning to learn features.	Edge Impulse

Did you know? You can bring your own model in PyTorch, Keras or scikit-learn.

Description	Author	Recommended
Object Detection (Images) Officially Supported Fine tune a pre-trained object detection model on your data. Good performance even with relatively small image datasets.	Edge Impulse
Object Detection (Images) - BrainChip Akida™ Officially Supported Fine tune a pre-trained object detection model on your data. Good performance even with relatively small image datasets. Only works with BrainChip AKD1000 MINI PCIe board.	BrainChip
FOMO-AD (Images) Enterprise Visual anomaly detection. Find outliers in new data. Extracts visual features using a pre-trained model on your data, and a Gaussian mixture model (GMM) models the shape of the features using a probability distribution. New data that is unlikely according to this model can be considered anomalous.	Edge Impulse
Object Detection (Images) Officially Supported Fine tune a pre-trained object detection model on your data. Good performance even with relatively small image datasets.	Edge Impulse
Object Detection (Images) - BrainChip Akida™ Officially Supported Fine tune a pre-trained object detection model on your data. Good performance even with relatively small image datasets. Only works with BrainChip AKD1000 MINI PCIe board.	BrainChip
Classification Officially Supported Learns patterns from data, and can apply these to new data. Great for categorizing movement or recognizing audio.	Edge Impulse
Transfer Learning (Images) Officially Supported Fine tune a pre-trained image classification model on your data. Good performance even with relatively small image datasets.	Edge Impulse
Regression Officially Supported Learns patterns from data, and can apply these to new data. Great for predicting numeric continuous values.	Edge Impulse
Transfer Learning (Keyword Spotting) Officially Supported Fine tune a pre-trained keyword spotting model on your data. Good performance even with relatively small keyword datasets.	Edge Impulse
Anomaly Detection (GMM) Professional Enterprise Find outliers in new data. A Gaussian mixture model (GMM) models the shape of data using a probability distribution. New data that is unlikely according to this model can be considered anomalous.	Edge Impulse
Anomaly Detection (K-means) Officially Supported Find outliers in new data. Good for recognizing unknown states, and to complement classifiers. Works best with low dimensionality features like the output of the spectral features block.	Edge Impulse
Classification - BrainChip Akida™ Officially Supported Learns patterns from data, and can apply these to new data. Great for categorizing movement or recognizing audio. Only works with BrainChip AKD1000 MINI PCIe board.	BrainChip
Transfer Learning (Images) - BrainChip Akida™ Officially Supported Fine tune a pre-trained image classification model on your data. Good performance even with relatively small image datasets. Only works with BrainChip AKD1000 MINI PCIe board.	BrainChip
FOMO-AD (Images) Enterprise Visual anomaly detection. Find outliers in new data. Extracts visual features using a pre-trained model on your data, and a Gaussian mixture model (GMM) models the shape of the features using a probability distribution. New data that is unlikely according to this model can be considered anomalous.	Edge Impulse

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Image data

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image

Image width

Image height

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Image

Name

Input axes (1)

image

Object Detection (Images)

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Input features

Image

Output features

5 (DC, INV, S1, S2, SM)

Output features

5 (DC, INV, S1, S2, SM)

Images
Officially Supported

Time series data
Officially Supported

Image
Officially Supported

Image
Officially Supported

Flatten
Officially Supported

Audio (MFCC)
Officially Supported

Audio (MFE)
Officially Supported

Spectral Analysis
Officially Supported

Spectrogram
Officially Supported

Audio (Syntiant)
Officially Supported

IMU (Syntiant)
Officially Supported

Raw Data
Officially Supported

Object Detection (Images)
Officially Supported

Object Detection (Images) - BrainChip Akida™
Officially Supported

FOMO-AD (Images)
Enterprise

Object Detection (Images)
Officially Supported

Object Detection (Images) - BrainChip Akida™
Officially Supported

Classification
Officially Supported

Transfer Learning (Images)
Officially Supported

Regression
Officially Supported

Transfer Learning (Keyword Spotting)
Officially Supported

Anomaly Detection (GMM)
Professional

Enterprise

Anomaly Detection (K-means)
Officially Supported

Classification - BrainChip Akida™
Officially Supported

Transfer Learning (Images) - BrainChip Akida™
Officially Supported

FOMO-AD (Images)
Enterprise

Image data

Image

Object Detection (Images)

Output features

No data collected yet

Description

Personal

Enterprise

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