Point Clouds Outlier Removal Method Based on Improved Mahalanobis and Completion

Qu, Chengzhi; Zhang, Yan; Huang, Kun; Wang, Shuang; Yang, Yang

doi:10.1109/lra.2022.3221315

Cited by 7 publications

(1 citation statement)

References 24 publications

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“…Some exemplary (relatively) recent applications of (squared) Mahalanobis distance can be found e.g. in Xu et al [301], Sun et al [302], Timmermann et al [303], Wauchope et al [304], Weinberger [305], Wen et al [306], Yang et al [307], Zhang et al [308], Burssens et al [309], Choi et al [310], Choi et al [311], Dahlin et al [312], Ebrahimi et al [313], Jeong et al [314], Kim et al [315], Nowakowski et al [316], Qu et al [317], Rabby et al [318], Sarno et al [319], Tang et al [320], Tsvieli & Weinberger [321], Zhang et al [322], Zhou et al [323]. Some exemplary (relatively) recent applications of generally non-separable (ordinary/classical) Bregman distances appear e.g.…”

Section: A Further Divergences and Friendsmentioning

confidence: 99%

A Precise Bare Simulation Approach to the Minimization of Some Distances. I. Foundations

Broniatowski¹,

Stummer

2023

IEEE Trans. Inform. Theory

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The constrained minimization (respectively maximization) of directed distances and of related generalized entropies is a fundamental task in information theory as well as in the adjacent fields of statistics, machine learning, artificial intelligence, signal processing and pattern recognition. In our previous paper "A precise bare simulation approach to the minimization of some distances. I. Foundations", we obtained such kind of constrained optima by a new dimension-free precise bare (pure) simulation method, provided basically that (i) the underlying directed distance is of f −divergence type, and that (ii) this can be connected to a light-tailed probability distribution in a certain manner. In the present paper, we extend this approach such that constrained optimization problems of a very huge amount of directed distances and generalized entropies -and beyond -can be tackled by a newly developed dimension-free extended bare simulation method, for obtaining both optima as well as optimizers. Almost no assumptions (like convexity) on the set of constraints are needed, within our discrete setup of arbitrary dimension, and our method is precise (i.e., converges in the limit). For instance, we cover constrained optimizations of arbitrary f −divergences, Bregman distances, scaled Bregman distances and weighted ℓr−distances. The potential for wide-spread applicability is indicated, too; in particular, we deliver many recent references for uses of the involved distances/divergences in various different research fields (which may also serve as an interdisciplinary interface).

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Section: A Further Divergences and Friendsmentioning

confidence: 99%

A Precise Bare Simulation Approach to the Minimization of Some Distances. I. Foundations

Broniatowski¹,

Stummer

2023

IEEE Trans. Inform. Theory

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Digital twin-driven smelting process management method for converter steelmaking

Fu,

Liu,

2024

J Intell Manuf

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The converter is an indispensable key equipment in the steel manufacturing industry. With the increasing demand for high-quality steel, there is an increasing demand for monitoring and controlling the status of the converter during the smelting process. Compared to other manufacturing industries, such as food processing and textile, converter steelmaking requires a larger keep-out zone due to its ultra-high temperatures and harsh smelting environment. This makes it difficult for personnel to fully understand, analyze, and manage the smelting process, resulting in low production efficiency and the inability to achieve consistently high-quality results. Aiming at the low virtual visualization level and insufficient monitoring ability of the converter steelmaking process, a process management method based on digital twin technology is proposed. Firstly, a digital twin system framework for full-process monitoring of converter steelmaking is proposed based on the analysis of the process characteristics of converter steelmaking. The proposed framework provides critical enabling technologies such as point cloud-based digital twin model construction, visual display, and steel endpoint analysis and prediction, to support full-process, high-fidelity intelligent monitoring. After conducting experiments, a digital twin-driven smelting process management system was developed to manage the entire smelting process. The system has proven to be effective as it increased the monthly production capacity by 77.7%. The waste of smelting materials has also been greatly reduced from 34% without the system to 7.8% with the system. Based on these results, it is evident that this system significantly enhances smelting efficiency and reduces both the costs and waste associated with the process.

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Skeleton-based coordinate system construction method for non-cooperative targets

Huang,

Zhang,

Chen

et al. 2024

Measurement

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Point Clouds Outlier Removal Method Based on Improved Mahalanobis and Completion

Cited by 7 publications

References 24 publications

A Precise Bare Simulation Approach to the Minimization of Some Distances. I. Foundations

A Precise Bare Simulation Approach to the Minimization of Some Distances. I. Foundations

Digital twin-driven smelting process management method for converter steelmaking

Skeleton-based coordinate system construction method for non-cooperative targets

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