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OBJECT CLASSIFICATION VIA PLANAR ABSTRACTION [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016 We present a supervised machine learning approach for classification of objects from sampled point data. The main idea consists in first abstracting the input object into planar parts at several scales, then discriminate between the different classes of ...
S. Oesau, F. Lafarge, P. Alliez
doaj +6 more sources
Likelihood-free inference via classification. [PDF]
Stat Comput, 2018 Increasingly complex generative models are being used across disciplines as they allow for realistic characterization of data, but a common difficulty with them is the prohibitively large computational cost to evaluate the likelihood function and thus to perform likelihood-based statistical inference.
Gutmann MU +3 more
europepmc +9 more sources
Entanglement classification via operator size
SciPost Physics Core, 2023 In this work, multipartite entanglement is classified by polynomials. I show that the operator size is closely related to the entanglement structure. Given a generic quantum state, I define a series of subspaces generated by operators of different sizes ...
Qi-Feng Wu
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Robust diagnostic classification via Q-learning [PDF]
Scientific Reports, 2021 Machine learning (ML) models have demonstrated the power of utilizing clinical instruments to provide tools for domain experts in gaining additional insights toward complex clinical diagnoses. In this context these tools desire two additional properties:
Victor Ardulov +7 more
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Materials Prediction via Classification Learning. [PDF]
Sci Rep, 2015 AbstractIn the paradigm of materials informatics for accelerated materials discovery, the choice of feature set (i.e. attributes that capture aspects of structure, chemistry and/or bonding) is critical. Ideally, the feature sets should provide a simple physical basis for extracting major structural and chemical trends and furthermore, enable rapid ...
Balachandran PV +3 more
europepmc +4 more sources
Robust Classification via Support Vector Machines [PDF]
Risks, 2022 Classification models are very sensitive to data uncertainty, and finding robust classifiers that are less sensitive to data uncertainty has raised great interest in the machine learning literature.
Alexandru V. Asimit +4 more
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POLSAR Image Classification via Clustering-WAE Classification Model
IEEE Access, 2018 Considering the clustering algorithms could explore the label information automatically, this paper proposes a new method in terms of polarimetric synthetic aperture radar (POLSAR) image classification, which named a clustering-wishart-auto-encoder (WAE)
Wen Xie, Ziwei Xie, Feng Zhao, Bo Ren
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Chrysanthemum classification via color space fusion transformer [PDF]
Scientific ReportsChrysanthemum is a traditional Chinese medicinal herb that contains significant medicinal and economic value. However, the medicinal and economic value of chrysanthemum differs depending on its regions and types.
Jian Jiang +6 more
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Trading via selective classification [PDF]
Proceedings of the Second ACM International Conference on AI in Finance, 2021 (8 pages, 6 figures, 4 tables, ICAIF'21)
Chalkidis, Nestoras, Savani, Rahul
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Trading via image classification [PDF]
Proceedings of the First ACM International Conference on AI in Finance, 2020 The art of systematic financial trading evolved with an array of approaches, ranging from simple strategies to complex algorithms all relying, primary, on aspects of time-series analysis. Recently, after visiting the trading floor of a leading financial institution, we noticed that traders always execute their trade orders while observing images of ...
Cohen, Naftali +2 more
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