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Now showing items 101-105 of 105
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 ...
BIO-CXRNET: a robust multimodal stacking machine learning technique for mortality risk prediction of COVID-19 patients using chest X-ray images and clinical data
(
Springer Science and Business Media Deutschland GmbH
, 2023 , Article)
Nowadays, quick, and accurate diagnosis of COVID-19 is a pressing need. This study presents a multimodal system to meet this need. The presented system employs a machine learning module that learns the required knowledge ...
Development of deep learning framework to predict physicochemical properties for Ionic liquids
(
Elsevier
, 2023 , Book chapter)
In this paper, a deep learning-based group contribution approach has been developed to identify the optimum structure for ionic liquids (ILs) and to maximize the CO2 absorption capacity. The suggested methodology demonstrates ...
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 ...