Blockchain technology, the foundation of cryptocurrencies like Bitcoin, has utility beyond finance due to its decentralized and secure transactional nature. However, today's blockchain networks face the challenge ...
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This paper presents a framework for parallel intelligent education that involves physical and virtual learning for a personalized learning *** especially focus on Chat Generative Pre-trained Transformer(ChatGPT)owing ...
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This paper presents a framework for parallel intelligent education that involves physical and virtual learning for a personalized learning *** especially focus on Chat Generative Pre-trained Transformer(ChatGPT)owing to its considerable potential to supplement regular class *** address the strengths and weaknesses of learning with ***,we discuss the challenges and solutions of the proposed parallel intelligent education with ChatGPT.
Geometric shape features have been widely used as strong predictors for image classification. Nevertheless, most existing classifiers such as deep neural networks (DNNs) directly leverage the statistical correlations ...
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ISBN:
(数字)9798331510831
ISBN:
(纸本)9798331510848
Geometric shape features have been widely used as strong predictors for image classification. Nevertheless, most existing classifiers such as deep neural networks (DNNs) directly leverage the statistical correlations between these shape features and target variables. However, these correlations can often be spurious and unstable across different environments (e.g., in different age groups, certain types of brain changes have unstable relations with neurodegenerative disease); hence leading to biased or inaccurate predictions. In this paper, we introduce a novel framework that for the first time develops invariant shape representation learning (ISRL) to further strengthen the robustness of image classifiers. In contrast to existing approaches that mainly derive features in the image space, our model ISRL is designed to jointly capture invariant features in latent shape spaces parameterized by deformable transformations. To achieve this goal, we develop a new learning paradigm based on invariant risk minimization (IRM) to learn invariant representations of image and shape features across multiple training distributions/environments. By embedding the features that are invariant with regard to target variables in different environments, our model consistently offers more accurate predictions. We validate our method by performing classification tasks on both simulated 2D images, real 3D brain and cine cardiovascular magnetic resonance images (MRIs). Our code is publicly available at https://***/tonmoy-hossain/ISRL.
A new optimal anti-disturbance sliding mode control approach for manipulators is proposed in this paper. Aiming at the difficulty of parameter selection of sliding mode controller for manipulators, instead of empirica...
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Machine Learning (ML) at the edge has the advantages of lower costs, reduced bandwidth needs, easy access, and high security. Machine Learning-based security protocols are hence suitable for providing added security a...
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Rolling bearings are the main components of rotating machines which are mostly damaged. Therefore, correct and quick fault diagnosis of rolling bearings is very necessary for maintenance. Nowadays, machine learning ha...
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Nowadays, large amounts of unstructured data are currently trending on social media and the Web. Text summarising is the process of extracting pertinent information in a concise manner without altering the content'...
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The Internet of Medical Things (IoMT), also known as Smart Healthcare, has seen incredible progress in the Smart Environment industry. A significant part of Industry 4.0 is Healthcare 4.0, which is transforming the me...
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We introduce a new variant of the art gallery problem that comes from safety issues. In this variant we are not interested in guard sets of smallest cardinality, but in guard sets with largest possible distances betwe...
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Unmanned Aerial Vehicles(UAVs)are gaining increasing attention in many fields,such as military,logistics,and hazardous site *** UAVs to assist communications is one of the promising applications and research *** futur...
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Unmanned Aerial Vehicles(UAVs)are gaining increasing attention in many fields,such as military,logistics,and hazardous site *** UAVs to assist communications is one of the promising applications and research *** future Industrial Internet places higher demands on communication *** easy deployment,dynamic mobility,and low cost of UAVs make them a viable tool for wireless communication in the Industrial ***,UAVs are considered as an integral part of Industry *** this article,three typical use cases of UAVs-assisted communications in Industrial Internet are first ***,the state-of-the-art technologies for drone-assisted communication in support of the Industrial Internet are *** to the current research,it can be assumed that UAV-assisted communication can support the future Industrial Internet to a certain ***,the potential research directions and open challenges in UAV-assisted communications in the upcoming future Industrial Internet are discussed.
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