Human-in-the-Loop Visual Re-ID For Population Size Estimation
New clustering method combines human input & statistical sampling to estimate cluster count more effectively. Users provide feedback to refine estimation process, overcoming algorithmic limitations.
This is a Plain English Papers summary of a research paper called Human-in-the-Loop Visual Re-ID for Population Size Estimation. If you like these kinds of analysis, you should subscribe to the AImodels.fyi newsletter or follow me on Twitter. Overview This paper presents a novel approach for estimating the number of clusters in a dataset using human input and a similarity-driven nested importance sampling technique. The method allows users to interactively guide the clustering process and provide feedback to refine the cluster count estimation. The proposed approach aims to address t...