Berlin’s Superbooth is probably the most significant date in the modular synth calendar. Seemingly every Eurorack developer and their CV-toting mother had some sort of presence at the Fez Centre this ...

Ultra Wide Band (UWB) technology has a wide range of applications in indoor positioning due to its high precision and strong anti-interference ability. However, in complex indoor environments, UWB ...

This is an implementation of the method described in the paper "Non-rigid point cloud registration using piece-wise tricubic polynomials as transformation model". This method can be used to register ...

To address the issues of feature mismatching and map overlap drift in simultaneous localization and mapping (SLAM) within degraded environments characterized by sparse geometric features or severe ...

Euclidean Minimum Spanning Trees using single-, sesqui-, and dual-tree Borůvka algorithms, which are quite fast in spaces of low intrinsic dimensionality, minimum spanning trees with respect to mutual ...

In this article we prove two characterizations of the Euclidean ball: (i) the only convex body in ℝ³ such that every normal plane bisects the volume (or surface area) is the Euclidean ball, (ii) the ...

Given the large volumes of sensitive information transmitted over the Internet, digital signatures are essential for verifying message authenticity and integrity. A key challenge is minimizing ...

Differential evolution (DE) is a robust optimizer designed for solving complex domain research problems in the computational intelligence community. In the present work, a multi-hybrid DE (MHDE) is ...

The goal of a machine learning regression problem is to predict a single numeric value. For example, you might want to predict the price of a particular make and model of a used car based on its ...

In this paper, a multitemporal SAR image despeckling based on non-local theory (NLG-MulSAR) algorithm is proposed, which is improved based on the basic framework of the ratio-based multitemporal SAR ...

Machine learning (ML) approaches are a collection of algorithms that attempt to extract patterns from data and to associate such patterns with discrete classes of samples in the data—e.g., given a ...