Support vector machines and word2vec for text classification with semantic features
J Lilleberg, Y Zhu, Y Zhang - 2015 IEEE 14th International …, 2015 - ieeexplore.ieee.org
With the rapid expansion of new available information presented to us online on a daily
basis, text classification becomes imperative in order to classify and maintain it. Word2vec …
basis, text classification becomes imperative in order to classify and maintain it. Word2vec …
3D skeleton-based human action classification: A survey
LL Presti, M La Cascia - Pattern Recognition, 2016 - Elsevier
In recent years, there has been a proliferation of works on human action classification from
depth sequences. These works generally present methods and/or feature representations …
depth sequences. These works generally present methods and/or feature representations …
On human motion prediction using recurrent neural networks
Human motion modelling is a classical problem at the intersection of graphics and computer
vision, with applications spanning human-computer interaction, motion synthesis, and …
vision, with applications spanning human-computer interaction, motion synthesis, and …
Efficient temporal sequence comparison and classification using gram matrix embeddings on a riemannian manifold
In this paper we propose a new framework to compare and classify temporal sequences.
The proposed approach captures the underlying dynamics of the data while avoiding …
The proposed approach captures the underlying dynamics of the data while avoiding …
Human skeleton representation for 3D action recognition based on complex network coding and LSTM
X Shen, Y Ding - Journal of Visual Communication and Image …, 2022 - Elsevier
Abstract 3D skeleton sequences contain more effective and discriminative information than
RGB video and are more suitable for human action recognition. Accurate extraction of …
RGB video and are more suitable for human action recognition. Accurate extraction of …
Representation, analysis, and recognition of 3D humans: A survey
Computer Vision and Multimedia solutions are now offering an increasing number of
applications ready for use by end users in everyday life. Many of these applications are …
applications ready for use by end users in everyday life. Many of these applications are …
Time series classification with echo memory networks
Echo state networks (ESNs) are randomly connected recurrent neural networks (RNNs) that
can be used as a temporal kernel for modeling time series data, and have been successfully …
can be used as a temporal kernel for modeling time series data, and have been successfully …
Real-time 3d human pose estimation without skeletal a priori structures
This study is about real-time 2D-3D human pose estimation without using the a priori
structure of the skeleton and with a low number of parameters for regression tasks. Current …
structure of the skeleton and with a low number of parameters for regression tasks. Current …
Double chain networks for monocular 3D human pose estimation
G Bai, Y Luo, X Pan, Y Wang, J Wang… - Image and Vision …, 2022 - Elsevier
The 2D-3D lifting task for Human Pose Estimation is a highly nonlinear mapping problem,
which requires mutual constraints among human joints. In this paper, we mainly discuss how …
which requires mutual constraints among human joints. In this paper, we mainly discuss how …
Attention-based spatio-temporal dependence learning network
Multivariate time series (MTS) classification is a challenging problem due to the complex
nature of data, especially for tasks with spatial dependencies such as three-dimensional …
nature of data, especially for tasks with spatial dependencies such as three-dimensional …