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Domain Adaptation with Adversarial Training and Graph Embeddings
Published 2018“…We propose a novel model that performs adversarial learning based domain adaptation to deal with distribution drifts and graph based semi-supervised learning to leverage unlabeled data within a single unified deep learning framework. …”
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D 2IA: User-defined interval analytics on distributed streams
Published 2019“…Spark, Flink) are working towards ultimate frameworks for streaming analytics. In order to achieve this goal, they started to offer extensions of SQL that incorporate stream-oriented primitives such as windowing and Complex Event Processing (CEP). …”
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A Blockchain Footprint for Authentication of IoT-Enabled Smart Devices in Smart Cities: State-of-the-Art Advancements, Challenges and Future Research Directions
Published 2022“…<p dir="ltr">The mechanisms based on the distributed environment have become an obvious choice for solutions, while they have not been limited only to a specific domain (i.e., crypto currency). …”
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Autocleandeepfood: auto-cleaning and data balancing transfer learning for regional gastronomy food computing
Published 2024“…We assess the performance of our framework on a real-world noisy public domain data set, ETH Food-101, and two novel web-collected datasets, MENA-150 and Pizza-Styles. …”
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I know you are watching me
Published 2017“…Motivated by the absence of any approach that accounts for such a challenge in the domain of cloud computing, we propose in this work an adaptive detection strategy that formulates a Stackelberg security game to enable the cloud system to optimally exploit its available amount of security resources to maximize the detection of distributed attacks, knowing that attackers have the ability to monitor the cloud system's strategies and adjust their own attack plans. …”
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Unsupervised Urban Tree Biodiversity Mapping from Street Imagery
Published 2025Get full text
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