4 citations · 6 across the 4 of their papers we have counts for
5 papers
Forming Local Intersections of Projections for Classifying and Searching Histopathology Images
Aditya Sriram, Shivam Kalra, Morteza Babaie +5
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…
Projectron -- A Shallow and Interpretable Network for Classifying Medical Images
Aditya Sriram, Shivam Kalra, H. R. Tizhoosh
This paper introduces the `Projectron' as a new neural network architecture that uses Radon projections to both classify and represent medical images. The motivation is to build sh…
Learning Autoencoded Radon Projections
Aditya Sriram, Shivam Kalra, H. R. Tizhoosh +1
Autoencoders have been recently used for encoding medical images. In this study, we design and validate a new framework for retrieving medical images by classifying Radon projectio…
Classification and Retrieval of Digital Pathology Scans: A New Dataset
Morteza Babaie, Shivam Kalra, Aditya Sriram +5
In this paper, we introduce a new dataset, \textbf{Kimia Path24}, for image classification and retrieval in digital pathology. We use the whole scan images of 24 different tissue t…
Learning Opposites Using Neural Networks
Shivam Kalra, Aditya Sriram, Shahryar Rahnamayan +1
Many research works have successfully extended algorithms such as evolutionary algorithms, reinforcement agents and neural networks using "opposition-based learning" (OBL). Two typ…