Browsing Computer Science by Title
Now showing items 507-526 of 549
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Towards subtyped program generation in F#
(ACM, 2011)Program Generation is the technique of combining code fragments to construct a program. In this work we report on our progress to extend F# with program generation constructs. Our prototype implementation uses a translation ... -
Towards test automation for certification tests in the banking domain
(IEEE, 2023)Software systems in the banking domain are business-critical applications that provide financial services. These systems are subject to rigorous certification tests, which are performed manually, and take weeks to complete. ... -
Tractable policy management framework for IoT
(SPIE, 2017)Due to the advancement in the technology, hype of connected devices (hence forth referred to as IoT) in support of automating the functionality of many domains, be it intelligent manufacturing or smart homes, have become ... -
TRIBE: Trust revision for information based on evidence
(IEEE, 2013)In recent years, the number of information sources available to support decision-making has increased dramatically. However, more information sources do not always mean higher precision in the fused information. This is ... -
TruSD: Trust framework for service discovery among IoT devices
(Elsevier, 2020-09-04)IoT provides an environment which enables access to a plethora of different services. In order to reach these services, devices need to decide if the providers are trustable or not. The decision to trust a node with whom ... -
Trust estimation and fusion of uncertain information by exploiting consistency
(IEEE, 2014)Agents may cooperate by communicating their opinions about various phenomena. These opinions are then fused by agents and used for informed decision-making. However, fusing opinions from diverse sources is not trivial - ... -
Trust estimation of sources over correlated propositions
(IEEE, 2018-09-05)This work analyzes the impact of correlated propositions when estimating the reporting behavior of information sources. These behavior estimates are critical for fusion, and traditional methods assume the propositions are ... -
Trust in robot–robot scaffolding
(IEEE, 2023-12-01)The study of robot trust in humans and other agents is not explored widely despite its importance for the near future human-robot symbiotic societies. Here, we propose that robots should trust partners that tend to reduce ... -
Trust me! I am a robot: an affective computational account of scaffolding in robot-robot interaction
(IEEE, 2021-08-08)Forming trust in a biological or artificial interaction partner that provides reliable strategies and employing the learned strategies to scaffold another agent are critical problems that are often addressed separately in ... -
Trust-based fusion of classifiers for static code analysis
(IEEE, 2014)Static code analysis tools automatically generate alerts for potential software faults that can lead to failures. However, developers are usually exposed to a large number of alerts. Moreover, some of these alerts are ... -
Trustworthiness assessment in multimodal human-robot interaction based on cognitive load
(IEEE, 2022)In this study, we extend our robot trust model into a multimodal setting in which the Nao robot leverages audio-visual data to perform a sequential multimodal pattern recalling task while interacting with a human partner ... -
Turkish WordNet KeNet
(Global WordNet Association, 2021)Currently, there are two available wordnets for Turkish: TR-wordnet of BalkaNet and KeNet. As the more comprehensive wordnet for Turkish, KeNet includes 76,757 synsets. KeNet has both intralingual semantic relations and ... -
Uncertainty assessment for detection of spoofing attacks to speaker verification systems using a Bayesian approach
(Elsevier, 2022-02)There has been tremendous progress in automatic speaker verification systems over the last decade. Still, spoofing attacks pose a significant challenge to their deployment. Even though there are various attack techniques ... -
Uncertainty-aware deep classifiers using generative models
(Association for the Advancement of Artificial Intelligence, 2020)Deep neural networks are often ignorant about what they do not know and overconfident when they make uninformed predictions. Some recent approaches quantify classification uncertainty directly by training the model to ... -
Uncertainty-aware situational understanding
(SPIE, 2019)Situational understanding is impossible without causal reasoning and reasoning under and about uncertainty, i.e. prob-abilistic reasoning and reasoning about the confidence in the uncertainty assessment. We therefore ... -
Use of line spectral frequencies for emotion recognition from speech
(IEEE, 2010)We propose the use of the line spectral frequency (LSF) features for emotion recognition from speech, which have not been been previously employed for emotion recognition to the best of our knowledge. Spectral features ... -
Using artificial neural networks to provide guidance in extending PL/SQL programs
(Springer, 2022-12)Extending legacy systems with new objects for contemporary functionality or technology can lead to architecture erosion. Misplacement of these objects gradually hampers the modular structure, of which documentation is ... -
Using convolutional neural networks to automate aircraft maintenance visual inspection
(MDPI, 2020-12)Convolutional Neural Networks combined with autonomous drones are increasingly seen as enablers of partially automating the aircraft maintenance visual inspection process. Such an innovative concept can have a significant ... -
Using different loss functions with YOLACT++ for real-time instance segmentation
(IEEE, 2023)In this paper, we study and analyze the performance of various loss functions on a recently proposed real-time instance segmentation algorithm, YOLACT++. In particular, we study the loss functions, including Huber Loss, ... -
Using eigenvoices and nearest-neighbors in HMM-based cross-lingual speaker adaptation with limited data
(IEEE, 2017-04)Cross-lingual speaker adaptation for speech synthesis has many applications, such as use in speech-to-speech translation systems. Here, we focus on cross-lingual adaptation for statistical speech synthesis systems using ...
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