10 citations · 10 across the 7 of their papers we have counts for
14 papers
Exploiting Explainable Metrics for Augmented SGD
Mahdi S. Hosseini, Mathieu Tuli, Konstantinos N. Plataniotis
Explaining the generalization characteristics of deep learning is an emerging topic in advanced machine learning. There are several unanswered questions about how learning under st…
HistoKT: Cross Knowledge Transfer in Computational Pathology
Ryan Zhang, Jiadai Zhu, Stephen Yang +7
The lack of well-annotated datasets in computational pathology (CPath) obstructs the application of deep learning techniques for classifying medical images. %Since pathologist time…
In Search of Probeable Generalization Measures
Jonathan Jaegerman, Khalil Damouni, Mahdi S. Hosseini +1
Understanding the generalization behaviour of deep neural networks is a topic of recent interest that has driven the production of many studies, notably the development and evaluat…
CONetV2: Efficient Auto-Channel Size Optimization for CNNs
Yi Ru Wang, Samir Khaki, Weihang Zheng +2
Neural Architecture Search (NAS) has been pivotal in finding optimal network configurations for Convolution Neural Networks (CNNs). While many methods explore NAS from a global sea…
Probeable DARTS with Application to Computational Pathology
Sheyang Tang, Mahdi S. Hosseini, Lina Chen +5
AI technology has made remarkable achievements in computational pathology (CPath), especially with the help of deep neural networks. However, the network performance is highly rela…
Reconsidering CO2 emissions from Computer Vision
Andre Fu, Mahdi S. Hosseini, Konstantinos N. Plataniotis
Climate change is a pressing issue that is currently affecting and will affect every part of our lives. It's becoming incredibly vital we, as a society, address the climate crisis…