Jan 18, 2024
1,047
0
2
References
- 1. Vehkaoja, Antti; Somppi, Sanni; Törnqvist, Heini; Valldeoriola Cardó, Anna; Kumpulainen, Pekka; Väätäjä, Heli; Majaranta, Päivi; Surakka, Veikko; Kujala, Miiamaaria; Vainio, Outi (2021), “Movement Sensor Dataset for Dog Behavior Classification”, Mendeley Data, V1, doi: 10.17632/vxhx934tbn.1
- 2. Kumpulainen, P., Cardó, A. V., Somppi, S., Törnqvist, H., Väätäjä, H., Majaranta, P., Gizatdinova, Y., Hoog Antink, C., Surakka, V., Kujala, M. V., Vainio, O., & Vehkaoja, A. (2021). Dog behaviour classification with movement sensors placed on the harness and the collar. Applied Animal Behaviour Science, 241, 105393. https://doi.org/10.1016/j.applanim.2021.105393
Rahardja and Shashikant like this. Please wait...
About This Project
Edge machine learning refers to the process of running embedded ML models on site using devices capable of collecting, processing, and recognizing patterns within collections of raw data. This project seeks to train one of such devices (Nicla SenseME) with dog data from the Earth Species' Bio-logger Ethogram Benchmark (BEBE). The board will be used as a smart dog collar, with its ML inferences controlling haptics vibrations in a bracelet wore by a person.
More Lab Notes From This Project
Browse Other Projects on Experiment
Related Projects
Dermatology AI Assistant to Empower Primary Care Providers in Zaatari Refugee Camp in Jordan
An AI-assisted dermatology tool for refugees, utilizing imaging and symptom questionnaires to improve diagnostic...
Generative Design of Programmable Metal-Binding Proteins for Bioremediation
The mining of heavy metals accounts for about 10% of global greenhouse gas emissions. Moreover, exposure...
How accurate is lyrebird vocal mimicry?
Lyrebirds are some of the world’s best vocal mimics and can accurately copy dozens of species in their Australian...
