Dec 10, 2015 · This paper proposes a novel application of Visual Assessment of Tendency (VAT)-based hierarchical clustering algorithms (VAT, iVAT, ...
Dec 15, 2015 · This paper proposes a novel application of Visual Assessment of Tendency (VAT)-based hierarchical clustering algorithms (VAT, iVAT, ...
Mar 1, 2017 · This paper proposes a novel application of Visual Assessment of Tendency (VAT)-based hierarchical clustering algorithms (VAT, iVAT, ...
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We introduce a new clustering based anomaly detection framework named iVAT+ and clusiVAT+ and use it for trajectory anomaly detection. This approach is based on ...
A visual-numeric approach to clustering and anomaly detection for trajectory data. D Kumar, JC Bezdek, S Rajasegarar, C Leckie, M Palaniswami. The Visual ...
A sequence of inc-iVAT/dec-iVAT images can be used for (visual) anomaly detection in evolving data streams and for sliding window based cluster assessment for ...
A visual-numeric approach to clustering and anomaly detection for trajectory data. Dheeraj Kumar; James C. Bezdek; Marimuthu Palaniswami. Original Article 10 ...
We propose an end-to-end deep learning framework for driving trajectory anomaly detection, called STDTB-AD.
This paper evaluates different similarity measures and clustering methodologies to catalog their strengths and weaknesses when utilized for the trajectory ...
Sep 18, 2024 · This paper presents a novel approach for trajectory anomaly detection using an autoregressive causal-attention model, termed LM-TAD.