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pro vyhledávání: '"Iquebal, Ashif"'
Active learning provides a framework to adaptively query the most informative experiments towards learning an unknown black-box function. Various approaches of active learning have been proposed in the literature, however, they either focus on explor
Externí odkaz:
http://arxiv.org/abs/2304.07665
Autor:
Afrin, Kahkashan, Iquebal, Ashif S., Karimi, Mostafa, Souris, Allyson, Lee, Se Yoon, Mallick, Bani K.
In recent biomedical scientific problems, it is a fundamental issue to integratively cluster a set of objects from multiple sources of datasets. Such problems are mostly encountered in genomics, where data is collected from various sources, and typic
Externí odkaz:
http://arxiv.org/abs/2003.07494
Publikováno v:
In Computational Materials Science May 2023 224
Akademický článek
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Advances in the image-based diagnostics of complex biological and manufacturing processes have brought unsupervised image segmentation to the forefront of enabling automated, on the fly decision making. However, most existing unsupervised segmentatio
Externí odkaz:
http://arxiv.org/abs/1811.00220
Autor:
Sikandar Iquebal, Ashif, Yadav, Aakash, Botcha, Bhaskar, Krishna Gorthi, Rama, Bukkapatnam, Satish
Publikováno v:
In Manufacturing Letters September 2022 33 Supplement:692-700
We present an approach for the detection of sharp change points (short-lived and persistent) in nonlinear and nonstationary dynamic systems under high levels of noise by tracking the local phase and amplitude synchronization among the components of a
Externí odkaz:
http://arxiv.org/abs/1701.00610
We report electron microscopy observations of the surface plastic flow in polishing of rough metal surfaces with a controlled spherical asperity structure. We show that asperity--abrasive sliding contacts exhibit viscous behavior, where the material
Externí odkaz:
http://arxiv.org/abs/1610.09719
Publikováno v:
In Procedia Manufacturing 2021 53:716-725
Publikováno v:
In Tribology International March 2020 143