Riemannian score-based generative modelling
Score-based generative models (SGMs) are a powerful class of generative models that
exhibit remarkable empirical performance. Score-based generative modelling (SGM) …
exhibit remarkable empirical performance. Score-based generative modelling (SGM) …
A survey on the internet of things security
K Zhao, L Ge - 2013 Ninth international conference on …, 2013 - ieeexplore.ieee.org
The security issues of the Internet of Things (IoT) are directly related to the wide application
of its system. Beginning with introducing the architecture and features of IoT security, this …
of its system. Beginning with introducing the architecture and features of IoT security, this …
Exploring techniques for vision based human activity recognition: Methods, systems, and evaluation
With the wide applications of vision based intelligent systems, image and video analysis
technologies have attracted the attention of researchers in the computer vision field. In …
technologies have attracted the attention of researchers in the computer vision field. In …
Kernel methods on Riemannian manifolds with Gaussian RBF kernels
In this paper, we develop an approach to exploiting kernel methods with manifold-valued
data. In many computer vision problems, the data can be naturally represented as points on …
data. In many computer vision problems, the data can be naturally represented as points on …
A Grassmann manifold handbook: Basic geometry and computational aspects
The Grassmann manifold of linear subspaces is important for the mathematical modelling of
a multitude of applications, ranging from problems in machine learning, computer vision and …
a multitude of applications, ranging from problems in machine learning, computer vision and …
Riemannian continuous normalizing flows
Normalizing flows have shown great promise for modelling flexible probability distributions
in a computationally tractable way. However, whilst data is often naturally described on …
in a computationally tractable way. However, whilst data is often naturally described on …
Advances in Computer Vision and Image Processing for Pattern Recognition: A Comprehensive Review
M Memari - International Journal of Engineering and Applied …, 2023 - papers.ssrn.com
Abstract Computer Vision, Image Processing, and Pattern Recognition are interdisciplinary
fields that have seen remarkable advancements in recent years. This article presents a …
fields that have seen remarkable advancements in recent years. This article presents a …
Accurate 3D action recognition using learning on the Grassmann manifold
In this paper we address the problem of modeling and analyzing human motion by focusing
on 3D body skeletons. Particularly, our intent is to represent skeletal motion in a geometric …
on 3D body skeletons. Particularly, our intent is to represent skeletal motion in a geometric …
Sparse coding and dictionary learning for symmetric positive definite matrices: A kernel approach
Recent advances suggest that a wide range of computer vision problems can be addressed
more appropriately by considering non-Euclidean geometry. This paper tackles the problem …
more appropriately by considering non-Euclidean geometry. This paper tackles the problem …
Continuous-discrete extended Kalman filter on matrix Lie groups using concentrated Gaussian distributions
In this paper we generalize the continuous-discrete extended Kalman filter (CD-EKF) to the
case where the state and the observations evolve on connected unimodular matrix Lie …
case where the state and the observations evolve on connected unimodular matrix Lie …