Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Our goal is to estimate a probability density based on discrete point data via segmentation techniques. Since point data may represent certain activities, such as crime, our method can be successfully used for detecting regions of high activity. In this work  design a binary segmentation version of the ll-known Maximum Penalized Likelihood Estimation (MPLE) model, as ll as a minimization algorithm based on thresholding dynamics originally proposed by Merriman et al. (The Computational Crystal Grors, pp. 73–83, 1992).  also present some computational examples, including one with actual residential burglary data from the San Fernando Valley.
['Tijana Kostic', 'Andrea L. Bertozzi']
I am writing a research paper on a idea Statistical Density Estimation Using Threshold Dynamics for Geometric Motion
[{"from": "human", "value": "I am writing a research paper on a idea Statistical Density Estimation Using Threshold Dynamics for Geometric Motion"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Our goal is to estimate a probability density based on discrete point data via segmentation techniques. Since point data may represent certain activities, such as crime, our method can be successfully used for detecting regions of high activity. In this work  design a binary segmentation version of the ll-known Maximum Penalized Likelihood Estimation (MPLE) model, as ll as a minimization algorithm based on thresholding dynamics originally proposed by Merriman et al. (The Computational Crystal Grors, pp. 73\u201383, 1992).  also present some computational examples, including one with actual residential burglary data from the San Fernando Valley."}]