Using K-Means clustering to export a NeRF for faster rendering in CG applications while preserving view-dependent appearance

With the current state-of-the-art research, exporting a NeRF to a mesh has the side effect of having to evaluate a Multi Layer Perceptron at render-time, causing a significant decrease in performance. We have found a way to use K-Means clustering to pre-compute values for this MLP, storing them in multiple octahedron maps for the GPU to fetch...

The Financial Benefit of Energy Consumption Behavior Diversity Within an Energy Community

Energy communities are not yet fully self sufficient, mostly due to financial factors. Efforts are made to reduce these factors. Communities invest in community-owned assets, which provide more savings compared to individually-owned assets. Prosumers share their loads for better energy distribution, this can provide a significant impact. A good...

Analysis of object tracking algorithms performance on event-based datasets

The event-based camera represents a revolutionary concept, having an asynchronous output. The pixels of dynamic vision sensors react to the brightness change, resulting in streams of events at very small intervals of time. This paper provides a model to track objects in neuromorphic datasets, using clustering. In addition, a non-linear filter is...

Comparison of Linguistic Language Classification based on Origin and Data Driven Language Classification using the IPA and Clustering

Language similarity is very useful for enrichment data in both Natural Lanuguage Processing (NLP) and Automatic Speech Recognition (ASR). A clustering algorithm could provide an efficient means to define language similarity in a data-driven way. This research investigates the relation between linguistic classification by origin and data driven...

MalPaCa Feature Combination: Which packet header features and combination thereof are the most generalizable, private and easy to extract to cluster malicious behavior?

MalPaCa is an unsupervised clustering tool, which the main purpose is to cluster unidirectional network connections based on network behavior. The clustering is only based on non-intrusive (private) packet features such as transport and network header fields, and thus it has a strong potential use-case. This paper focuses on feature extraction...

The influence of sequence length on the clustering performance of MalPaCA

MalPaCa is a novel, unsupervised clustering algorithm, which creates based on the network flow of a software a behavioral profile representing its actual capabilities. One of the key variables affecting is performance and usability is the sequence length or how many packets it analyzes in order to group a connection to a cluster. This article...

Multimodal Interface for DNA Alignment of Sequences

Major research efforts in Bioinformatics include sequence alignment, gene finding, genome assembly, protein structure alignment, protein structure prediction, prediction of gene expression and protein-protein interactions, and the modeling of evolution. To perform these specific tasks different tools are used. Using these tools separately is a...