Home ›
Entities
› academia
› Building robust models for Human Activity Recognition from raw accelerometers data using Gated Recurrent Units and Long Short Term Memory Neural Networks
Building robust models for Human Activity Recognition from raw accelerometers data using Gated Recurrent Units and Long Short Term Memory Neural Networks
Research article (2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2019) · cited 30× · AI/ML
Building robust models for Human Activity Recognition from raw accelerometers data using Gated Recurrent Units and Long Short Term Memory Neural Networks
Summary
Building robust models for Human Activity Recognition from raw accelerometers data using Gated Recurrent Units and Long Short Term Memory Neural Networks is a scholarly article[1].
Key Facts
Building robust models for Human Activity Recognition from raw accelerometers data using Gated Recurrent Units and Long Short Term Memory Neural Networks's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Building robust models for Human Activity Recognition from raw accelerometers data using Gated Recurrent Units and Long Short Term Memory Neural Networks. Retrieved May 24, 2026, from https://4ort.xyz/entity/building-robust-models-for-human-activity-recognition-from-raw-accelerometers-data-using-gated-recurrent-units-and-long-
MLA“Building robust models for Human Activity Recognition from raw accelerometers data using Gated Recurrent Units and Long Short Term Memory Neural Networks.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/building-robust-models-for-human-activity-recognition-from-raw-accelerometers-data-using-gated-recurrent-units-and-long-.
BibTeX@misc{4ortxyz_building-robust-models-for-human-activity-recognition-from-raw-accelerometers-data-using-gated-recurrent-units-and-long-_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Building robust models for Human Activity Recognition from raw accelerometers data using Gated Recurrent Units and Long Short Term Memory Neural Networks}}, year = {2026}, url = {https://4ort.xyz/entity/building-robust-models-for-human-activity-recognition-from-raw-accelerometers-data-using-gated-recurrent-units-and-long-}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Building robust models for Human Activity Recognition from raw accelerometers data using Gated Recurrent Units and Long Short Term Memory Neural Networks — https://4ort.xyz/entity/building-robust-models-for-human-activity-recognition-from-raw-accelerometers-data-using-gated-recurrent-units-and-long- (retrieved 2026-05-24)