activity
20172022
most citedMCUa: Multi-level Context and Uncertainty aware Dynamic Deep Ensemble for Breast Cancer Histology Image Classification

76 citations · 118 across the 14 of their papers we have counts for

collaborators

27 papers

cs.LG20221 cited

Controlled Dropout for Uncertainty Estimation

Mehedi Hasan, Abbas Khosravi, Ibrahim Hossain +2

Uncertainty quantification in a neural network is one of the most discussed topics for safety-critical applications. Though Neural Networks (NNs) have achieved state-of-the-art per…

cs.CV20211 cited

A Comprehensive Study on Torchvision Pre-trained Models for Fine-grained Inter-species Classification

Feras Albardi, H M Dipu Kabir, Md Mahbub Islam Bhuiyan +3

This study aims to explore different pre-trained models offered in the Torchvision package which is available in the PyTorch library. And investigate their effectiveness on fine-gr…

cs.CV2021

What happens in Face during a facial expression? Using data mining techniques to analyze facial expression motion vectors

Mohamad Roshanzamir, Roohallah Alizadehsani, Mahdi Roshanzamir +4

One of the most common problems encountered in human-computer interaction is automatic facial expression recognition. Although it is easy for human observer to recognize facial exp…

cs.CV202176 cited

MCUa: Multi-level Context and Uncertainty aware Dynamic Deep Ensemble for Breast Cancer Histology Image Classification

Zakaria Senousy, Mohammed M. Abdelsamea, Mohamed Medhat Gaber +4

Breast histology image classification is a crucial step in the early diagnosis of breast cancer. In breast pathological diagnosis, Convolutional Neural Networks (CNNs) have demonst…

cs.LG202112 cited

Uncertainty-Aware Credit Card Fraud Detection Using Deep Learning

Maryam Habibpour, Hassan Gharoun, Mohammadreza Mehdipour +7

Countless research works of deep neural networks (DNNs) in the task of credit card fraud detection have focused on improving the accuracy of point predictions and mitigating unwant…

cs.CV20211 cited

An Uncertainty-Aware Deep Learning Framework for Defect Detection in Casting Products

Maryam Habibpour, Hassan Gharoun, AmirReza Tajally +4

Defects are unavoidable in casting production owing to the complexity of the casting process. While conventional human-visual inspection of casting products is slow and unproductiv…