1 citations · 2 across the 3 of their papers we have counts for
4 papers
Beyond Measurement Metrics: A Human-Centered Framework for Semantic Validation of Network Traffic Classification
Igor Cherepanov, David Sessler, Alex Ulmer +2
Machine learning (ML) has become the dominant approach for network traffic classification, achieving very high predictive performance. However, a model is only valuable if it learn…
Interactive Analysis of Global Explanations using Aggregated Class Activation Maps for Network Data
Igor Cherepanov, David Sessler, Alex Ulmer +3
Recent machine learning (ML) advances have demonstrated that deep learning (DL) achieves impressive results in different application domains, including the classification of comput…
Towards the Visualization of Aggregated Class Activation Maps to Analyse the Global Contribution of Class Features
Igor Cherepanov, David Sessler, Alex Ulmer +2
Deep learning (DL) models achieve remarkable performance in classification tasks. However, models with high complexity can not be used in many risk-sensitive applications unless a…
Visual-Interactive Similarity Search for Complex Objects by Example of Soccer Player Analysis
Jürgen Bernard, Christian Ritter, David Sessler +3
The definition of similarity is a key prerequisite when analyzing complex data types in data mining, information retrieval, or machine learning. However, the meaningful definition…