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Št. zadetkov: 2
LLM in the loop: a framework for contextualizing counterfactual segment perturbations in point clouds
Veljka Kocic, Niko Lukač, Dzemail Rozajac, Stefan Schweng, Christoph Gollob, Arne Nothdurft, Karl Stampfer, Javier Del Ser, Andreas Holzinger
Izvirni znanstveni članek
Oznake: umetna inteligenca;podatki v oblaku;veliki jezikovni modeli;explainable AI;point cloud data;counterfactual reasoning;LiDAR;3D point cloud data;interpretability;human-centered AI;large language models;K-nearest neighbors;
Point Cloud Data analysis has seen a major leap forward with the introduction of PointNet algorithms, revolutionizing how we process 3D environments. Yet, despite these advancements, key challenges remain, particularly in optimizing segment perturbations to influence model outcomes in a controlled a ...
Leto: 2025 Vir: Fakulteta za elektrotehniko, računalništvo in informatiko (UM FERI)
Enhancing trust in automated 3D point cloud data interpretation through explainable counterfactuals
Andreas Holzinger, Niko Lukač, Dzemail Rozajac, Emil Johnston, Veljka Kocic, Bernhard Hoerl, Christoph Gollob, Arne Nothdurft, Karl Stampfer, Stefan Schweng, Javier Del Ser
Izvirni znanstveni članek
Oznake: explainable AI;point cloud data;counterfactual reasoning;information fusion;interpretability;human-centered AI;
This paper introduces a novel framework for augmenting explainability in the interpretation of point cloud data by fusing expert knowledge with counterfactual reasoning. Given the complexity and voluminous nature of point cloud datasets, derived predominantly from LiDAR and 3D scanning technologies, ...
Leto: 2025 Vir: Fakulteta za elektrotehniko, računalništvo in informatiko (UM FERI)
Št. zadetkov: 2
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