4 results match your criteria Acm Computing Surveys[Journal]

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Multi-Label Active Learning Algorithms for Image Classification: Overview and Future Promise.

ACM Comput Surv 2020 Jun 13;53(2). Epub 2020 Mar 13.

Soochow University, China.

Image classification is a key task in image understanding, and multi-label image classification has become a popular topic in recent years. However, the success of multi-label image classification is closely related to the way of constructing a training set. As active learning aims to construct an effective training set through iteratively selecting the most informative examples to query labels from annotators, it was introduced into multi-label image classification. Read More

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Multi-Robot Assembly Strategies and Metrics.

ACM Comput Surv 2018 Feb 1;51(1). Epub 2018 Jan 1.

U.S. National Institute of Standards and Technology.

We present a survey of multi-robot assembly applications and methods and describe trends and general insights into the multi-robot assembly problem for industrial applications. We focus on fixtureless assembly strategies featuring two or more robotic systems. Such robotic systems include industrial robot arms, dexterous robotic hands, and autonomous mobile platforms, such as automated guided vehicles. Read More

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February 2018

A Survey of Physics-Based Attack Detection in Cyber-Physical Systems.

ACM Comput Surv 2018 ;51

National Institute of Standards and Technology.

Monitoring the "physics" of cyber-physical systems to detect attacks is a growing area of research. In its basic form a security monitor creates time-series models of sensor readings for an industrial control system and identifies anomalies in these measurements in order to identify potentially false control commands or false sensor readings. In this paper, we review previous work on physics-based anomaly detection based on a unified taxonomy that allows us to identify limitations and unexplored challenges, and propose new solutions. Read More

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January 2018

Privacy in the Genomic Era.

ACM Comput Surv 2015 Sep;48(1)

Indiana University at Bloomington.

Genome sequencing technology has advanced at a rapid pace and it is now possible to generate highly-detailed genotypes inexpensively. The collection and analysis of such data has the potential to support various applications, including personalized medical services. While the benefits of the genomics revolution are trumpeted by the biomedical community, the increased availability of such data has major implications for personal privacy; notably because the genome has certain essential features, which include (but are not limited to) an association with traits and certain diseases, identification capability (e. Read More

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September 2015
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