Search Results for author:
Found 6 papers, 3 papers with code
Comprehensive Comparison of Deep Learning Models for Lung and COVID-19 Lesion Segmentation in CT scans
In this paper, an extensive comparison of DL models for lung and COVID-19 lesion segmentation in Computerized Tomography (CT) scans is presented, which can also be used as a benchmark for testing medical image segmentation models.
A Makefile for Developing Containerized LaTeX Technical Documents
We propose a Makefile for developing containerized $\LaTeX$ technical documents.
Software Engineering
Sparsely Activated Networks: A new method for decomposing and compressing data
We lastly present Sparsely Activated Networks (SANs) that consist of kernels with shared weights that, during encoding, are convolved with the input and then passed through a sparse activation function.
Sparsely Activated Networks
We lastly present Sparsely Activated Networks (SANs) that consist of kernels with shared weights that, during encoding, are convolved with the input and then passed through a sparse activation function.
Signal2Image Modules in Deep Neural Networks for EEG Classification
Deep learning has revolutionized computer vision utilizing the increased availability of big data and the power of parallel computational units such as graphical processing units.
Deep Learning in Cardiology
The medical field is creating large amount of data that physicians are unable to decipher and use efficiently.
