18 citations · 19 across the 4 of their papers we have counts for
4 papers
ALFA -- Leveraging All Levels of Feature Abstraction for Enhancing the Generalization of Histopathology Image Classification Across Unseen Hospitals
Milad Sikaroudi, Maryam Hosseini, Shahryar Rahnamayan +1
We propose an exhaustive methodology that leverages all levels of feature abstraction, targeting an enhancement in the generalizability of image classification to unobserved hospit…
Evolutionary Computation in Action: Feature Selection for Deep Embedding Spaces of Gigapixel Pathology Images
Azam Asilian Bidgoli, Shahryar Rahnamayan, Taher Dehkharghanian +2
One of the main obstacles of adopting digital pathology is the challenge of efficient processing of hyperdimensional digitized biopsy samples, called whole slide images (WSIs). Exp…
Ranking Loss and Sequestering Learning for Reducing Image Search Bias in Histopathology
Pooria Mazaheri, Azam Asilian Bidgoli, Shahryar Rahnamayan +1
Recently, deep learning has started to play an essential role in healthcare applications, including image search in digital pathology. Despite the recent progress in computer visio…
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…