Computational intelligence and neuroscience
Jan 6, 2022
This paper deals with adaptive nonlinear identification and trajectory tracking problem for model free nonlinear systems via parametric neural network (PNN). Firstly, a more effective PNN identifier is developed to obtain the unknown system dynamics,...
Digitalisation of the healthcare sector promises to revolutionise patient healthcare globally. From the different technologies, virtual tools including artificial intelligence, blockchain, virtual, and augmented reality, to name but a few, are provid...
This paper presents deterioration level estimation based on convolutional neural networks using a confidence-aware attention mechanism for infrastructure inspection. Spatial attention mechanisms try to highlight the important regions in feature maps ...
Over the past decade, artificial intelligence (AI) and machine learning (ML) have become the breakthrough technology most anticipated to have a transformative effect on pharmaceutical research and development (R&D). This is partially driven by revolu...
The use of machine learning (ML) allows us to automate and scale the decision-making processes. The key to this automation is the development of ML models that generalize training data toward unseen data. Such models can become extremely versatile an...
Computer methods and programs in biomedicine
Dec 31, 2021
Deep learning methods, especially convolutional neural networks, have advanced the breast lesion classification task using breast ultrasound (BUS) images. However, constructing a highly-accurate classification model still remains challenging due to c...
An important area in a gathering place is a region attracting the constant attention of people and has evident visual features, such as a flexible stage or an open-air show. Finding such areas can help security supervisors locate the abnormal regions...
The current approach to using machine learning (ML) algorithms in healthcare is to either require clinician oversight for every use case or use their predictions without any human oversight. We explore a middle ground that lets ML algorithms abstain ...
Generative adversarial network (GAN) has been regarded as a promising solution to many machine learning problems, and it comprises of a generator and discriminator, determining patterns and anomalies in the input data. However, GANs have several comm...
BMC medical informatics and decision making
Dec 30, 2021
OBJECTIVE: Relation extraction (RE) is a fundamental task of natural language processing, which always draws plenty of attention from researchers, especially RE at the document-level. We aim to explore an effective novel method for document-level med...
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