Fusing RGB and Thermal Imagery with Channel State Information for Abnormal Activity Detection Using Multimodal Bidirectional LSTM

In this paper, we present a multimodal deep model for detection of abnormal activity, based on bidirectional Long Short-Term Memory neural networks (LSTM). The proposed model exploits three different input modalities: RGB imagery, thermographic imagery and Channel State Information from Wi-Fi signal...

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Detalles Bibliográficos
Autores principales: Bakalos, Nikolaos, Voulodimos, Athanasios, Doulamis, Nikolaos, Doulamis, Anastasios, Papasotiriou, Kassiani, Bimpas, Matthaios
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7888295/
http://dx.doi.org/10.1007/978-3-030-69781-5_6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7888295/
http://dx.doi.org/10.1007/978-3-030-69781-5_6

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