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Found 8 papers, 0 papers with code
A Framework for Building Point Cloud Cleaning, Plane Detection and Semantic Segmentation
This paper presents a framework to address the challenges involved in building point cloud cleaning, plane detection, and semantic segmentation, with the ultimate goal of enhancing building modeling.
Machine Learning and Feature Ranking for Impact Fall Detection Event Using Multisensor Data
This highlights the potential of our approach to enhance fall detection systems and improve the overall safety and well-being of individuals at risk of falls.
SPDGAN: A Generative Adversarial Network based on SPD Manifold Learning for Automatic Image Colorization
In this work, we propose a fully automatic colorization approach based on Symmetric Positive Definite (SPD) Manifold Learning with a generative adversarial network (SPDGAN) that improves the quality of the colorization results.
MR-STGN: Multi-Residual Spatio Temporal Graph Network Using Attention Fusion for Patient Action Assessment
Accurate assessment of patient actions plays a crucial role in healthcare as it contributes significantly to disease progression monitoring and treatment effectiveness.
D-STGCNT: A Dense Spatio-Temporal Graph Conv-GRU Network based on transformer for assessment of patient physical rehabilitation
To achieve this goal, a new graph-based model, the Dense Spatio-Temporal Graph Conv-GRU Network with Transformer, is introduced.
Movienet: A Movie Multilayer Network Model using Visual and Textual Semantic Cues
Motivated by these limitations, we introduce in this work a multilayer network model to capture the narration of a movie based on its script, its subtitles, and the movie content.
A General Framework for Complex Network-Based Image Segmentation
In order to segment the image into meaningful connected components, this paper proposes an image segmentation general framework using complex networks based community detection algorithms.
Multilayer Network Model of Movie Script
Network models have been increasingly used in the past years to support summarization and analysis of narratives, such as famous TV series, books and news.
