A survey of image labelling for computer vision applications
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 …
training data to solve computer vision problems. The recent rise of deep learning algorithms …
ANIMO: annotation of biomed image modalities
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 …
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
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 …
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 …
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 …
have achieved impressive successes in knowledge and pattern discovery across diverse …