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Found 5 papers, 0 papers with code
Forming Local Intersections of Projections for Classifying and Searching Histopathology Images
In this paper, we propose a novel image descriptor called Forming Local Intersections of Projections (FLIP) and its multi-resolution version (mFLIP) for representing histopathology images.
Projectron -- A Shallow and Interpretable Network for Classifying Medical Images
This paper introduces the `Projectron' as a new neural network architecture that uses Radon projections to both classify and represent medical images.
Learning Autoencoded Radon Projections
Autoencoders have been recently used for encoding medical images.
Classification and Retrieval of Digital Pathology Scans: A New Dataset
In this paper, we introduce a new dataset, \textbf{Kimia Path24}, for image classification and retrieval in digital pathology.
Learning Opposites Using Neural Networks
In this paper, we introduce an approach to learn type-II opposites from the given inputs and their outputs using the artificial neural networks (ANNs).
