Semi-supervised Sorting via Deep Feature Extraction and Density Based Clustering with User Feedback

Pascal Graf, Morris Ohrnberger, Dominic Dötterer, Nicolaj C. Stache

Abstract: Efficient data sorting remains a significant challenge when faced with unknown object characteristics or appearances. Unsupervised learning struggles with contextual nuances and subjective human perspectives, complicating the sorting process. In this paper, we propose a novel semi-supervised algorithm merging deep feature extraction, density-based clustering, and user feedback to address this complexity.

External IDs:dblp:conf/hci/GrafODS24