Jan 18, 2024
1,080
0
4
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
tonyclake, jacksonmeet25, and 2 others 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.
Browse Other Projects on Experiment
Related Projects
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...
Designing ultrastable carbonic anhydrase with deep generative models and high-throughput assays
To minimize the impact of CO2 emissions on life on earth, we need technologies for carbon capture exceeding...
Single-Cell Multiomic Profiling of Killifish for Cell-Cultured Seafood
Cultivated seafood research lags behind in large part due to limited data, especially on a single-cell level...
