Efficient Spatio-Temporal Signal Recognition on Edge Devices Using PointLCA-Net
SM Takaghaj, J Sampson - arXiv preprint arXiv:2411.14585, 2024 - arxiv.org
Recent advancements in machine learning, particularly through deep learning architectures
like PointNet, have transformed the processing of three-dimensional (3D) point clouds,
significantly improving 3D object classification and segmentation tasks. While 3D point
clouds provide detailed spatial information, spatio-temporal signals introduce a dynamic
element that accounts for changes over time. However, applying deep learning techniques
to spatio-temporal signals and deploying them on edge devices presents challenges …
like PointNet, have transformed the processing of three-dimensional (3D) point clouds,
significantly improving 3D object classification and segmentation tasks. While 3D point
clouds provide detailed spatial information, spatio-temporal signals introduce a dynamic
element that accounts for changes over time. However, applying deep learning techniques
to spatio-temporal signals and deploying them on edge devices presents challenges …
Efficient Spatio-Temporal Signal Recognition on Edge Devices Using PointLCA-Net
S Mahmoodi Takaghaj, J Sampson - arXiv e-prints, 2024 - ui.adsabs.harvard.edu
Recent advancements in machine learning, particularly through deep learning architectures
like PointNet, have transformed the processing of three-dimensional (3D) point clouds,
significantly improving 3D object classification and segmentation tasks. While 3D point
clouds provide detailed spatial information, spatio-temporal signals introduce a dynamic
element that accounts for changes over time. However, applying deep learning techniques
to spatio-temporal signals and deploying them on edge devices presents challenges …
like PointNet, have transformed the processing of three-dimensional (3D) point clouds,
significantly improving 3D object classification and segmentation tasks. While 3D point
clouds provide detailed spatial information, spatio-temporal signals introduce a dynamic
element that accounts for changes over time. However, applying deep learning techniques
to spatio-temporal signals and deploying them on edge devices presents challenges …
