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Human Activity Recognition Based on Deep-Temporal Learning Using Convolution Neural Networks Features and Bidirectional Gated Recurrent Unit With Features Selection
Research article (IEEE Access, 2023) · cited 49× · AI/ML
Human Activity Recognition Based on Deep-Temporal Learning Using Convolution Neural Networks Features and Bidirectional Gated Recurrent Unit With Features Selection
Summary
Human Activity Recognition Based on Deep-Temporal Learning Using Convolution Neural Networks Features and Bidirectional Gated Recurrent Unit With Features Selection is a scholarly article[1].
Key Facts
Human Activity Recognition Based on Deep-Temporal Learning Using Convolution Neural Networks Features and Bidirectional Gated Recurrent Unit With Features Selection's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Human Activity Recognition Based on Deep-Temporal Learning Using Convolution Neural Networks Features and Bidirectional Gated Recurrent Unit With Features Selection. Retrieved May 24, 2026, from https://4ort.xyz/entity/human-activity-recognition-based-on-deep-temporal-learning-using-convolution-neural-networks-features-and-bidirectional-
MLA“Human Activity Recognition Based on Deep-Temporal Learning Using Convolution Neural Networks Features and Bidirectional Gated Recurrent Unit With Features Selection.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/human-activity-recognition-based-on-deep-temporal-learning-using-convolution-neural-networks-features-and-bidirectional-.
BibTeX@misc{4ortxyz_human-activity-recognition-based-on-deep-temporal-learning-using-convolution-neural-networks-features-and-bidirectional-_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Human Activity Recognition Based on Deep-Temporal Learning Using Convolution Neural Networks Features and Bidirectional Gated Recurrent Unit With Features Selection}}, year = {2026}, url = {https://4ort.xyz/entity/human-activity-recognition-based-on-deep-temporal-learning-using-convolution-neural-networks-features-and-bidirectional-}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Human Activity Recognition Based on Deep-Temporal Learning Using Convolution Neural Networks Features and Bidirectional Gated Recurrent Unit With Features Selection — https://4ort.xyz/entity/human-activity-recognition-based-on-deep-temporal-learning-using-convolution-neural-networks-features-and-bidirectional- (retrieved 2026-05-24)
