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Discrete point cloud objects lack sufficient shape descriptors of 3D geometries. In this paper, we present a novel method for aggregating hypothetical curves in point clouds. Sequences of connected points (curves) are initially grouped by…

Computer Vision and Pattern Recognition · Computer Science 2021-07-30 Tiange Xiang , Chaoyi Zhang , Yang Song , Jianhui Yu , Weidong Cai

Capsule networks (CapsNets) have recently shown promise to excel in most computer vision tasks, especially pertaining to scene understanding. In this paper, we explore CapsNet's capabilities in optical flow estimation, a task at which…

Computer Vision and Pattern Recognition · Computer Science 2020-11-10 Vinoj Jayasundara , Debaditya Roy , Basura Fernando

Computability theory is used to evaluate the complexity of classifying various kinds of Lebesgue spaces and associated isometric isomorphism problems.

Logic · Mathematics 2019-07-01 Tyler Brown , Alexander G. Melnikov , Timothy H. McNicholl

This is a survey on the state-of-the-art of the classification of finite-dimensional complex Hopf algebras. This general question is addressed through the consideration of different classes of such Hopf algebras. Pointed Hopf algebras…

Quantum Algebra · Mathematics 2014-04-01 Nicolás Andruskiewitsch

Most image-search approaches today are based on the text based tags associated with the images which are mostly human generated and are subject to various kinds of errors. The results of a query to the image database thus can often be…

Machine Learning · Computer Science 2010-08-03 Ankit Garg , Rahul Dwivedi , Krishna Asawa

LiDAR-based 3D object detection is an important task for autonomous driving and current approaches suffer from sparse and partial point clouds of distant and occluded objects. In this paper, we propose a novel two-stage approach, namely…

Computer Vision and Pattern Recognition · Computer Science 2020-12-23 Yanan Zhang , Di Huang , Yunhong Wang

Recent work on deep clustering has found new promising methods also for constrained clustering problems. Their typically pairwise constraints often can be used to guide the partitioning of the data. Many problems however, feature…

Machine Learning · Computer Science 2023-05-22 Jonas K. Falkner , Lars Schmidt-Thieme

We propose a similarity-based method, using the similarity between nodes, to address the problem of classification in partially labeled networks. The basic assumption is that two nodes are more likely to be categorized into the same class…

Data Analysis, Statistics and Probability · Physics 2010-10-05 Qian-Ming Zhang , Ming-Sheng Shang , Linyuan Lu

Capsule networks (see e.g. Hinton et al., 2018) aim to encode knowledge and reason about the relationship between an object and its parts. In this paper we specify a \emph{generative} model for such data, and derive a variational algorithm…

Machine Learning · Computer Science 2022-03-16 Alfredo Nazabal , Nikolaos Tsagkas , Christopher K. I. Williams

Every polygon $P$ can be companioned by a cap polygon $\hat P$ such that $P$ and $\hat P$ serve as two parts of the boundary surface of a polyhedron $V$. Pairs of vertices on $P$ and $\hat P$ are identified successively to become vertices…

Computational Geometry · Computer Science 2024-11-27 Mercedes Sandu , Shuyi Weng , Jade Zhang

In this paper we give a complete classification of cyclically graded semisimple Lie algebras that afford cuspidal character sheaves and determine the support of the cuspidal character sheaves. This constitutes a major step towards the…

Representation Theory · Mathematics 2025-12-24 Wille Liu , Kari Vilonen , Ting Xue

In this paper we give a complete characterization of the statistical equivalence classes of CEGs and of staged trees. We are able to show that all graphical representations of the same model share a common polynomial description. Then,…

Statistics Theory · Mathematics 2017-05-29 Christiane Görgen , Jim Q. Smith

We classify all compact simply connected biquotients of dimension 4 and 5. In particular, all pairs of groups $(G,H)$ and embeddings $H\rightarrow G\times G$ giving rise to a particular biquotient are classified.

Differential Geometry · Mathematics 2016-08-24 Jason DeVito

We study edge-to-edge tilings of the sphere by edge congruent pentagons, under the assumption that there are tiles with all vertices having degree 3. We develop the technique of neighborhood tilings and apply the technique to completely…

Metric Geometry · Mathematics 2013-04-16 Ka Yue Cheuk , Ho Man Cheung , Min Yan

In this paper, we consider a simple class of stratified spaces -- 2-complexes. We present an algorithm that learns the abstract structure of an embedded 2-complex from a point cloud sampled from it. We use tools and inspiration from…

Computational Geometry · Computer Science 2023-05-05 Yossi Bokor Bleile

Terrestrial laser scanning (TLS) can obtain tree point cloud with high precision and high density. Efficient classification of wood points and leaf points is essential to study tree structural parameters and ecological characteristics. By…

Computer Vision and Pattern Recognition · Computer Science 2021-08-03 Jingqian Sun , Pei Wang , Zhiyong Gao , Zichu Liu , Yaxin Li , Xiaozheng Gan

The rapid increase in data on galaxy images at low and high redshift calls for re-examination of the classification schemes and for new automatic objective methods. Here we present a classification method by Artificial Neural Networks. We…

Astrophysics · Physics 2007-05-23 Ofer Lahav

We give a complete derived equivalence classification of all nonstandard representation-infinite domestic selfinjective algebras over an algebraically closed field. As a consequence, also a complete stable equivalence classification of…

Representation Theory · Mathematics 2007-05-23 Rafal Bocian , Thorsten Holm , Andrzej Skowronski

We study the degrees of selector functions related to the degrees in which a rigid computable structure is relatively computably categorical. It is proved that for some structures such degrees can be represented as the unions of upper cones…

Logic · Mathematics 2023-05-31 I. Sh. Kalimullin

Integrated Gradients (IG) and PatternAttribution (PA) are two established explainability methods for neural networks. Both methods are theoretically well-founded. However, they were designed to overcome different challenges. In this work,…

Machine Learning · Computer Science 2020-09-02 Robert Schwarzenberg , Steffen Castle
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