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Costas Panagiotakis
In this paper, we present a general version of polygonal fitting problem called Unconstrained Polygonal Fitting (UPF). Our goal is to represent a given 2D shape S with an N-vertex polygonal curve P with a known number of vertices, so that the Intersectio...
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Kayo Okabe and Atsuyuki Okabe
An open-space ratio is often used as a first basic metric to examine the distribution of open space in urbanized areas. Originally, the open-space ratio was defined as the ratio of the area of open space (unbuilt area) to the area of its building site. I...
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Christopher Tsang, James Parker and David Glew
A substantial number of dwellings in the UK have poor building fabric, leading to higher carbon emissions, fuel expenses, and the risk of cold homes. To tackle these challenges, domestic energy efficiency policies are being implemented. One effective app...
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Josue-Rafael Montes-Martínez, Hugo Jiménez-Hernández, Ana-Marcela Herrera-Navarro, Luis-Antonio Díaz-Jiménez, Jorge-Luis Perez-Ramos and Julio-César Solano-Vargas
Artificial vision system applications have generated significant interest as they allow information to be obtained through one or several of the cameras that can be found in daily life in many places, such as parks, avenues, squares, houses, etc. When th...
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Zixin Feng, Teligeng Yun, Yu Zhou, Ruirui Zheng and Jianjun He
Geometric mean metric learning (GMML) algorithm is a novel metric learning approach proposed recently. It has many advantages such as unconstrained convex objective function, closed form solution, faster computational speed, and interpretability over oth...
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Rianna Burnham and David Duffus
Organisms use multi-modal, scale-dependent, sensory information to decipher their surroundings. This can include, for example, recognizing the presence of con- or heterospecifics, including a predatory threat, the presence and abundance of prey, or navig...
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Yingying Liang, Peng Zhao and Yimeng Wang
Deep learning has undergone significant progress for machinery fault diagnosis in the Industrial Internet of Things; however, it requires a substantial amount of labeled data. The lack of sufficient fault samples in practical applications remains a chall...
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Antonio Lopez-Martinez-Carrasco, Jose M. Juarez, Manuel Campos and Bernardo Canovas-Segura
Subgroup Discovery (SD) is a supervised data mining technique for identifying a set of relations (subgroups) among attributes from a dataset with respect to a target attribute. Two key components of this technique are (i) the metric used to quantify a su...
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Shumin Lai, Longjun Huang, Ping Li, Zhenzhen Luo, Jianzhong Wang and Yugen Yi
In this paper, we present a novel unsupervised feature selection method termed robust matrix factorization with robust adaptive structure learning (RMFRASL), which can select discriminative features from a large amount of multimedia data to improve the p...
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W. Charles Kerfoot, Gary Swain, Luis M. Verissimo, Erin Johnston, Carol A. MacLennan, Daniel Schneider and Noel R. Urban
Over a century ago, copper mills on the Keweenaw Peninsula of Lake Superior sluiced 64 million metric tonnes (MMT) of tailings into coastal waters, creating a metal-rich ?halo?. Here we show that relatively small discharges can spread widely in time and ...
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