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Single-shot retinal image enhancement using untrained and pretrained neural networks priors integrated with analytical image priors
(
Elsevier
, 2022 , Article)
Retinal images acquired using fundus cameras are often visually blurred due to imperfect imaging conditions, refractive medium turbidity, and motion blur. In addition, ocular diseases such as the presence of cataracts also ...
An active learning method for diabetic retinopathy classification with uncertainty quantification
(
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 ...
Security and privacy of internet of medical things: A contemporary review in the age of surveillance, botnets, and adversarial ML
(
Elsevier
, 2022 , Article Review)
Internet of Medical Things (IoMT) supports traditional healthcare systems by providing enhanced scalability, efficiency, reliability, and accuracy of healthcare services. It enables the development of smart hardware as ...
Making federated learning robust to adversarial attacks by learning data and model association
(
Elsevier
, 2022 , Article)
One of the key challenges in federated learning (FL) is the detection of malicious parameter updates. In a typical FL setup, the presence of malicious client(s) can potentially demolish the overall training of the shared ...