datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
harupfall-accelerometer-images-plots-resultant-blur-noise
Dataset Card for "harupfall-accelerometer-images-plots-resultant-blur-noise"
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accelerometer-fall-axis-data
Dataset Card for "accelerometer-fall-axis-data"
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harupfall-accelerometer-images-plots-resultant-alpaca
Dataset Card for "harupfall-accelerometer-images-plots-resultant-alpaca"
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harupfall-accelerometer-images-plots-resultant
Dataset Card for "harupfall-accelerometer-images-plots-resultant"
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accelerometer-fall-axis-plots-alpacaaccelerometer_raw_emotion_recognition_smartphone_sensorsEmotion Recognition ML on the Basis of Smartphone Accelerometer Sensors ✨
Hi,
I tried to find a correlation between emotional states (or vibes, as they are referred to in the deployed mobile applications) and the way the user moves the phone while typing (for example, a message). I wanted to represent these emotions then in color (an accompanying color bubble after each message on WhatsApp, for example).
I collected data from myself in different emotional states, ending up with around an hour… See the full description on the dataset page: https://huggingface.co/datasets/wolfeiq/accelerometer_raw_emotion_recognition_smartphone_sensors.harupfall-accelerometer-data-actual
Dataset Card for "harupfall-accelerometer-data-actual"
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accelerometer-fall-axis-plotsharupfall-accelerometer-images-alpaca
Dataset Card for "harupfall-accelerometer-images-alpaca"
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harupfall-accelerometer-images-actual
Dataset Card for "harupfall-accelerometer-images-actual"
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accelerometer-fall-axis-data_alpaca
Dataset Card for "accelerometer-fall-axis-data_alpaca"
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harupfall-accelerometer-data-alpaca
Dataset Card for "harupfall-accelerometer-data-alpaca"
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2D_GPS_Accelerometeraccelerometer-fall-plots-imagesaccelerometerData
Hand Detection Training Data
This folder contains sensor data collected from mobile devices for training the hand detection model.
Overview
The dataset includes accelerometer and gyroscope readings from 2 subjects, each holding a device with both their left and right hands. This data is used to train the Random Forest classifier that achieves 94.6% accuracy in detecting which hand is holding the device.
Directory Structure
hand_data/
├── accelerometer/… See the full description on the dataset page: https://huggingface.co/datasets/rockerritesh/accelerometerData.cattle_accelerometer_datacattle_accelerometer_dataaccelerometer