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20122023
most citedAutomated Pavement Crack Segmentation Using U-Net-based Convolutional Neural Network

289 citations · 464 across the 17 of their papers we have counts for

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Showing 2020Show all

6 papers · 1 filter

physics.app-ph2020★ 1 cited

Machine learning and high-throughput robust design of P3HT-CNT composite thin films for high electrical conductivity

Daniil Bash, Yongqiang Cai, Vijila Chellappan +16

Combining high-throughput experiments with machine learning allows quick optimization of parameter spaces towards achieving target properties. In this study, we demonstrate that ma…

cs.LG2020

A robust low data solution: dimension prediction of semiconductor nanorods

Xiaoli Liu, Yang Xu, Jiali Li +4

Precise control over dimension of nanocrystals is critical to tune the properties for various applications. However, the traditional control through experimental optimization is sl…

math.OC2020★ 47 cited

A Unified Single-loop Alternating Gradient Projection Algorithm for Nonconvex-Concave and Convex-Nonconcave Minimax Problems

Zi Xu, Huiling Zhang, Yang Xu +1

Much recent research effort has been directed to the development of efficient algorithms for solving minimax problems with theoretical convergence guarantees due to the relevance o…

cs.CL2020★ 5 cited

Application of Pre-training Models in Named Entity Recognition

Yu Wang, Yining Sun, Zuchang Ma +3

Named Entity Recognition (NER) is a fundamental Natural Language Processing (NLP) task to extract entities from unstructured data. The previous methods for NER were based on machin…

cs.NI2020

To schedule or not to schedule: when no-scheduling can beat the best-known flow scheduling algorithm in datacenter networks

Soheil Abbasloo, Yang Xu, H. Jonathan Chao

Conventional wisdom for minimizing the average flow completion time (AFCT) in the datacenter network (DCN), where flow sizes are highly variable, would suggest scheduling every ind…

cs.CV2020★ 289 cited

Automated Pavement Crack Segmentation Using U-Net-based Convolutional Neural Network

Stephen L. H. Lau, Edwin K. P. Chong, Xu Yang +1

Automated pavement crack image segmentation is challenging because of inherent irregular patterns, lighting conditions, and noise in images. Conventional approaches require a subst…