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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
(
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
(
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 ...
AI-enabled remote monitoring of vital signs for COVID-19: methods, prospects and challenges
(
Springer
, 2021 , Article)
The COVID-19 pandemic has overwhelmed the existing healthcare infrastructure in many parts of the world. Healthcare professionals are not only over-burdened but also at a high risk of nosocomial transmission from COVID-19 ...
Advance Warning Methodologies for COVID-19 Using Chest X-Ray Images
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Coronavirus disease 2019 (COVID-19) has rapidly become a global health concern after its first known detection in December 2019. As a result, accurate and reliable advance warning system for the early diagnosis of COVID-19 ...
Audio-Based Drone Detection and Identification Using Deep Learning Techniques with Dataset Enhancement through Generative Adversarial Networks
(
MDPI
, 2021 , Article)
Drones are becoming increasingly popular not only for recreational purposes but in day-to-day applications in engineering, medicine, logistics, security and others. In addition to their useful applications, an alarming ...
Edge Detection with multi-scale representation and refined Network
(
Institution of Engineering and Technology
, 2022 , Conference Paper)
Edge detection is a representation of boundaries between objects and regions in an image. Due to the variations of types, scales, intensities as well as background, the detection of these boundaries represents a challenge ...
Convolutional Sparse Support Estimator-Based COVID-19 Recognition from X-Ray Images
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Coronavirus disease (COVID-19) has been the main agenda of the whole world ever since it came into sight. X-ray imaging is a common and easily accessible tool that has great potential for COVID-19 diagnosis and prognosis. ...
Computational methods for automated analysis of corneal nerve images: Lessons learned from retinal fundus image analysis
(
Elsevier
, 2020 , Article Review)
Corneal and retinal imaging provide a descriptive view of the nerve and vessel structure present inside the human eye, in a non-invasive manner. This helps in ocular, or other, disease identification and diagnosis. However, ...
Smartphone-based diabetic retinopathy severity classification using convolution neural networks
(
Springer
, 2021 , Conference Paper)
With diabetes growing at an alarming rate, changes in the retina causes a condition called diabetic retinopathy which eventually leads to blindness. Early detection of diabetic retinopathy is the best way to provide good ...