As the basic task of point cloud analysis, classification is fundamental but always challenging. To address some unsolved problems existing methods, we propose a network that captures geometric features clouds for better representations. achieve this, on one hand, enrich information points in low-level 3D space explicitly. On other apply CNN-based structures high-level feature spaces to learn l...

We propose a modification of the classical proximal point algorithm for finding zeroes of a maximal monotone operator in a Hilbert space. In particular, an approximate proximal point iteration is used to construct a hyperplane which strictly separates the current iterate from the solution set of the problem. This step is then followed by a projection of the current iterate onto the separating h...

Cryptographic protocols are useful for engineering trust in transactions. There are several languages for describing these protocols, but these tend to capture the communications from the perspective of an individual role. In contrast, traditional protocol descriptions as found in a state of nature tend to employ a whole-protocol description, resulting in an impedance mismatch. In this paper we...

Aperiodic point sets (or tilings) which can be obtained by the method of cut and projection from higher dimensional periodic sets play an important role for the description of quasicrystals. Their topological invariants can be computed using the higher dimensional periodic structure. We report on the results obtained for the cohomology groups of projection point patterns supplemented by explici...

The projection method obtains non-trivial point processes from higher dimensional Poisson point processes by constructing a random subset of the higher dimensional space and projecting the points of the Poisson process lying in that set onto the lower dimensional region. This paper presents a review of this method related to spatial point processes as well as some examples of its applications. ...