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COVID-19 infection map generation and detection from chest X-ray images
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Springer Science and Business Media Deutschland GmbH
, 2021 , Article)
Computer-aided diagnosis has become a necessity for accurate and immediate coronavirus disease 2019 (COVID-19) detection to aid treatment and prevent the spread of the virus. Numerous studies have proposed to use Deep ...
Deep learning-based middle cerebral artery blood flow abnormality detection using flow velocity waveform derived from transcranial Doppler ultrasound
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Elsevier
, 2023 , Article)
Since the brain is unlike any other organ in that it cannot store energy and has a high metabolic demand, constant blood flow is essential for healthy brain function. The maximum flow velocity waveform that is produced by ...
DL-CRC: Deep learning-based chest radiograph classification for covid-19 detection: A novel approach
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Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
With the exponentially growing COVID-19 (coronavirus disease 2019) pandemic, clinicians continue to seek accurate and rapid diagnosis methods in addition to virus and antibody testing modalities. Because radiographs such ...
A cost-effective 3d acquisition and visualization framework for cultural heritage
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Springer Science and Business Media Deutschland GmbH
, 2021 , Conference Paper)
Museums and cultural institutions, in general, are in a constant challenge of adding more value to their collections. The attractiveness of assets is practically tightly related to their value obeying the offer and demand ...
NDDNet: a deep learning model for predicting neurodegenerative diseases from gait pattern
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Springer Nature
, 2023 , Article)
Neurodegenerative diseases damage neuromuscular tissues and deteriorate motor neurons which affects the motor capacity of the patient. Particularly the walking gait is greatly influenced by the deterioration process. Early ...
Employing machine learning techniques in monitoring autocorrelated profiles
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Springer Science and Business Media Deutschland GmbH
, 2023 , Article)
In profile monitoring, it is usually assumed that the observations between or within each profile are independent of each other. However, this assumption is often violated in manufacturing practice, and it is of utmost ...
Disaster related social media content processing for sustainable cities
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Elsevier
, 2021 , Article)
The current study offers a hybrid convolutional neural networks (CNN) model that filters relevant posts and categorises them into several humanitarian classifications using both character and word embedding of textual ...
An active learning method for diabetic retinopathy classification with uncertainty quantification
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Springer Science and Business Media Deutschland GmbH
, 2022 , Article)
In recent years, deep learning (DL) techniques have provided state-of-the-art performance in medical imaging. However, good quality (annotated) medical data is in general hard to find due to the usually high cost of medical ...
Recent progress in generative adversarial networks applied to inversely designing inorganic materials: A brief review
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Elsevier B.V.
, 2022 , Other)
Generative adversarial networks (GANs) are deep generative models (GMs) that have recently attracted attention owing to their impressive performance in generating completely novel images, text, music, and speech. Recently, ...
Dairy Cow Rumination Detection: A Deep Learning Approach
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Springer Science and Business Media Deutschland GmbH
, 2020 , Conference Paper)
Cattle activity is an essential index for monitoring health and welfare of the ruminants. Thus, changes in the livestock behavior are a critical indicator for early detection and prevention of several diseases. Rumination ...