Cargando…
Video-Based Human Activity Recognition Using Deep Learning Approaches
Due to its capacity to gather vast, high-level data about human activity from wearable or stationary sensors, human activity recognition substantially impacts people’s day-to-day lives. Multiple people and things may be seen acting in the video, dispersed throughout the frame in various places. Beca...
Autores principales: | Surek, Guilherme Augusto Silva, Seman, Laio Oriel, Stefenon, Stefano Frizzo, Mariani, Viviana Cocco, Coelho, Leandro dos Santos |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10386633/ https://www.ncbi.nlm.nih.gov/pubmed/37514677 http://dx.doi.org/10.3390/s23146384 |
Ejemplares similares
-
Optimized EWT-Seq2Seq-LSTM with Attention Mechanism to Insulators Fault Prediction
por: Klaar, Anne Carolina Rodrigues, et al.
Publicado: (2023) -
Machine Fault Detection Using a Hybrid CNN-LSTM Attention-Based Model
por: Borré, Andressa, et al.
Publicado: (2023) -
Group Method of Data Handling Using Christiano–Fitzgerald Random Walk Filter for Insulator Fault Prediction
por: Stefenon, Stefano Frizzo, et al.
Publicado: (2023) -
Static Attitude Determination Using Convolutional Neural Networks
por: dos Santos, Guilherme Henrique, et al.
Publicado: (2021) -
Semi-ProtoPNet Deep Neural Network for the Classification of Defective Power Grid Distribution Structures
por: Stefenon, Stefano Frizzo, et al.
Publicado: (2022)