Browsing by Subject "Deep Learning"
Now showing items 1-20 of 55
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(2020-04-16)Ambulatory devices and Image-based IoT devices have permeated our every-day life. Such technologies allow the continuous monitoring of individuals’ behavioral signals and expressions in every-day life, affording us new ...
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(2022-04-22)The guiding design principle behind humans building machines has been the repeated execution of a particular task in a precise and efficient manner. While we have systems that can solve tasks ranging from the relatively ...
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Receiving insight into the thoughts and feelings of a recruiter is vital to understanding effective job interviews. To ascertain categorical responses and speech patterns, audio and visual data from mock job interviews ...
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(2023-05-16)News Discourse Profiling is a sub-task of Discourse Parsing, which aims to analyze each sentence’s event-related role and has been proven useful in several downstream tasks. Complex feature extractors are widely employed ...
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(2023-05-16)News Discourse Profiling is a sub-task of Discourse Parsing, which aims to analyze each sentence’s event-related role and has been proven useful in several downstream tasks. Complex feature extractors are widely employed ...
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(2023-05-16)News Discourse Profiling is a sub-task of Discourse Parsing, which aims to analyze each sentence’s event-related role and has been proven useful in several downstream tasks. Complex feature extractors are widely employed ...
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(2021-12-07)Deep learning algorithms are highly energy and memory-intensive as their performance increases with an increasing amount of data. Moore’s law coming to an end and the ever-increasing demand for high computational power by ...
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(2023-06-08)Various advanced reactor designs proposed in recent years envision deployment scenarios which feature reactor operations with significantly reduced staffing or even completely autonomous frameworks to reduce the operations ...
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(2023-06-08)Various advanced reactor designs proposed in recent years envision deployment scenarios which feature reactor operations with significantly reduced staffing or even completely autonomous frameworks to reduce the operations ...
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(2020-07-21)Artificial intelligence and machine learning have transformed many industries. However, the oil and gas industry is lagging in AI adaption. Currently, with the low oil prices and a considerable performance gap in the oil ...
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Automated Construction Work Package Decision-Making Model Using RSMeans and LSTM Based Deep Learning (2022-03-29)Construction projects involve complicated workflows with efficient resource management. One of the methods for successful project planning is Work Packaging (WP.) Composition of the WP has been done by human understanding, ...
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(2022-12-10)Machine learning has succeeded in real-world applications from image classification, speech recognition, to beating human champion in Go games. To accelerate the development of different ap-plications, automated machine ...
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(2020-10-27)Drug resistance is a fundamental barrier to developing robust antimicrobial and anticancer therapies. Its first sign was observed in the 1940s, soon after discovering penicillin, the first modern antibiotic. This dissertation ...
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(2019-11-26)Failing to keep track of the construction progress in time and making current construction progress falling behind the schedule will cause a significant loss of time and money. Monitoring the progress of the constructing ...
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(2023-05-10)Memristor crossbars (MC) are being widely adopted in research for energy-efficient deep learning (DL) due to their low power and fast switching characteristics, and nonvolatile nature. In particular, MCs have been demonstrated ...
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(2023-05-10)State Highway Agencies (SHAs) collect a significant amount of digital data on highway projects during different project phases, including bid tabulations and Daily Work Reports (DWRs). However, SHAs do not fully take ...
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(2022-04-11)The promise of deep learning is to discover rich, hierarchical models that represent probability distributions over the kinds of data encountered in artificial intelligence applications, such as natural images, audio ...
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Monte Carlo path tracing is one of the most desirable methods to render an image from three-dimensional data thanks to its innate ability to portray physically realistic and desirable phenomena such as soft shadows, motion ...
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(2019-04-16)Video object segmentation is gaining increased research and commercial importance in recent times from no checkout lines in Amazon Go stores to autonomous vehicles operating on roads. Efficient operation for such use cases ...
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(2022-01-06)Machine learning techniques are widely used to build models for applications in healthcare. These models typically predict likelihood of a particular patient outcome in a given setting. For clinical utility, these models ...