445 citations · 897 across the 7 of their papers we have counts for
5 papers · 1 filter
Breast Cancer Classification from Histopathological Images with Inception Recurrent Residual Convolutional Neural Network
Md Zahangir Alom, Chris Yakopcic, Tarek M. Taha +1
The Deep Convolutional Neural Network (DCNN) is one of the most powerful and successful deep learning approaches. DCNNs have already provided superior performance in different moda…
Microscopic Nuclei Classification, Segmentation and Detection with improved Deep Convolutional Neural Network (DCNN) Approaches
Md Zahangir Alom, Chris Yakopcic, Tarek M. Taha +1
Due to cellular heterogeneity, cell nuclei classification, segmentation, and detection from pathological images are challenging tasks. In the last few years, Deep Convolutional Neu…
The History Began from AlexNet: A Comprehensive Survey on Deep Learning Approaches
Md Zahangir Alom, Tarek M. Taha, Christopher Yakopcic +6
Deep learning has demonstrated tremendous success in variety of application domains in the past few years. This new field of machine learning has been growing rapidly and applied i…
Deep Versus Wide Convolutional Neural Networks for Object Recognition on Neuromorphic System
Md Zahangir Alom, Theodore Josue, Md Nayim Rahman +3
In the last decade, special purpose computing systems, such as Neuromorphic computing, have become very popular in the field of computer vision and machine learning for classificat…
Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image Segmentation
Md Zahangir Alom, Mahmudul Hasan, Chris Yakopcic +2
Deep learning (DL) based semantic segmentation methods have been providing state-of-the-art performance in the last few years. More specifically, these techniques have been success…