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An Efficient and Scalable Deep Learning Approach for Road Damage Detection


Authors:  SadraNaddaf-sh, M-MahdiNaddaf-Sh, AmirR.Kashani....
Published date-11/18/2020
Tasks:  DataAugmentation, ImageAugmentation, ObjectDetection, RoadDamageDetection

Abstract: Pavement condition evaluation is essential to time the preventative or rehabilitative actions and control distress propagation. Failing to conduct timely evaluations can lead to severe structural and financial loss of …

TJU-DHD: A Diverse High-Resolution Dataset for Object Detection


Authors:  YanweiPang, JialeCao, YazhaoLi....
Published date-11/18/2020
Tasks:  ObjectDetection, PedestrianDetection

Abstract: Vehicles, pedestrians, and riders are the most important and interesting objects for the perception modules of self-driving vehicles and video surveillance. However, the state-of-the-art performance of detecting such important objects …

FixBi: Bridging Domain Spaces for Unsupervised Domain Adaptation


Authors:  JaeminNa, HeechulJung, HyungJinChang....
Published date-11/18/2020
Tasks:  DomainAdaptation, UnsupervisedDomainAdaptation

Abstract: Unsupervised domain adaptation (UDA) methods for learning domain invariant representations have achieved remarkable progress. However, few studies have been conducted on the case of large domain discrepancies between a source …

Statistical model-based evaluation of neural networks


Authors:  SandipanDas, PrakashB.Gohain, AlirezaM.Javid....
Published date-11/18/2020

Abstract: Using a statistical model-based data generation, we develop an experimental setup for the evaluation of neural networks (NNs). The setup helps to benchmark a set of NNs vis-a-vis minimum-mean-square-error (MMSE) …

A User's Guide to Calibrating Robotics Simulators


Authors:  BhairavMehta, AnkurHanda, DieterFox....
Published date-11/17/2020
Tasks:  DecisionMaking

Abstract: Simulators are a critical component of modern robotics research. Strategies for both perception and decision making can be studied in simulation first before deployed to real world systems, saving on …

Revisiting the Sample Complexity of Sparse Spectrum Approximation of Gaussian Processes


Authors:  QuangMinhHoang, TrongNghiaHoang, HaiPham....
Published date-11/17/2020
Tasks:  GaussianProcesses

Abstract: We introduce a new scalable approximation for Gaussian processes with provable guarantees which hold simultaneously over its entire parameter space. Our approximation is obtained from an improved sample complexity analysis …

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