activity
20162025
most citedCOVID_MTNet: COVID-19 Detection with Multi-Task Deep Learning Approaches

83 citations · 136 across the 4 of their papers we have counts for

collaborators
Showing 2018 · cs.CVShow all

6 papers · 2 filters

cs.CV2018

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…

cs.CV2018

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…

cs.CV2018

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…

cs.CV2018

Effective Quantization Approaches for Recurrent Neural Networks

Md Zahangir Alom, Adam T Moody, Naoya Maruyama +2

Deep learning, and in particular Recurrent Neural Networks (RNN) have shown superior accuracy in a large variety of tasks including machine translation, language understanding, and…

cs.CV2018

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…

cs.CV2018

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…