A survey of image labelling for computer vision applications

C Sager, C Janiesch, P Zschech - Journal of Business Analytics, 2021 - Taylor & Francis
Supervised machine learning methods for image analysis require large amounts of labelled
training data to solve computer vision problems. The recent rise of deep learning algorithms …

ANIMO: annotation of biomed image modalities

JT Trabucco, P Li, C Arighi, D Raciti… - 2021 IEEE …, 2021 - ieeexplore.ieee.org
Figures within biomedical articles present essential evidence of the relevance of a
publication in a curation workflow. In particular, visual cues of the image modality or …

Utilizing a responsive web portal for studying disc tracing agreement in retinal images

A Sarhan, A Swift, A Gorner, J Rokne, R Alhajj… - Plos one, 2021 - journals.plos.org
Glaucoma is a leading cause of blindness worldwide whose detection is based on multiple
factors, including measuring the cup to disc ratio, retinal nerve fiber layer and visual field …

[PDF][PDF] Integrating Deep Learning and Image Processing Techniques into a Hybrid Model for Glaucoma Detection.

A Sarhan - 2021 - prism.ucalgary.ca
This thesis involved collecting retinal images from a local clinic in Calgary, Alberta. All
images have been anonymous and hence there is no way to identify corresponding …

Building Deep Neural Network Models Leveraging Scarce and Heterogeneous Annotations

AD Chakravarthy - 2021 - search.proquest.com
Recently, inductive learning approaches using deep convolutional neural network models
have achieved impressive successes in knowledge and pattern discovery across diverse …