A review on extreme learning machine
Extreme learning machine (ELM) is a training algorithm for single hidden layer feedforward
neural network (SLFN), which converges much faster than traditional methods and yields …
neural network (SLFN), which converges much faster than traditional methods and yields …
COVID-19 CT image recognition algorithm based on transformer and CNN
X Fan, X Feng, Y Dong, H Hou - Displays, 2022 - Elsevier
Novel corona virus pneumonia (COVID-19) broke out in 2019, which had a great impact on
the development of world economy and people's lives. As a new mainstream image …
the development of world economy and people's lives. As a new mainstream image …
Covid-19 classification by FGCNet with deep feature fusion from graph convolutional network and convolutional neural network
Abstract (Aim) COVID-19 is an infectious disease spreading to the world this year. In this
study, we plan to develop an artificial intelligence based tool to diagnose on chest CT …
study, we plan to develop an artificial intelligence based tool to diagnose on chest CT …
A five-layer deep convolutional neural network with stochastic pooling for chest CT-based COVID-19 diagnosis
Abstract Till August 17, 2020, COVID-19 has caused 21.59 million confirmed cases in more
than 227 countries and territories, and 26 naval ships. Chest CT is an effective way to detect …
than 227 countries and territories, and 26 naval ships. Chest CT is an effective way to detect …
Multiple sclerosis identification by convolutional neural network with dropout and parametric ReLU
Multiple sclerosis is a condition affecting brain and/or spinal cord. Based on deep learning,
this study aims to develop an improved convolutional neural network system. We collected …
this study aims to develop an improved convolutional neural network system. We collected …
Neural network based brain tumor detection using wireless infrared imaging sensor
PM Shakeel, TEE Tobely, H Al-Feel… - IEEE …, 2019 - ieeexplore.ieee.org
Now-a-days image processing placed an important role for recognizing various diseases
such as breast, lung, and brain tumors in earlier stage for giving the appropriate treatment …
such as breast, lung, and brain tumors in earlier stage for giving the appropriate treatment …
A seven-layer convolutional neural network for chest CT-based COVID-19 diagnosis using stochastic pooling
(Aim) COVID-19 pandemic causes numerous death tolls till now. Chest CT is an effective
imaging sensor system to make accurate diagnosis.(Method) This article proposed a novel …
imaging sensor system to make accurate diagnosis.(Method) This article proposed a novel …
ResGNet-C: A graph convolutional neural network for detection of COVID-19
The widely spreading COVID-19 has caused thousands of hundreds of mortalities over the
world in the past few months. Early diagnosis of the virus is of great significance for both of …
world in the past few months. Early diagnosis of the virus is of great significance for both of …
COVID-19 diagnosis via DenseNet and optimization of transfer learning setting
COVID-19 is an ongoing pandemic disease. To make more accurate diagnosis on COVID-
19 than existing approaches, this paper proposed a novel method combining DenseNet and …
19 than existing approaches, this paper proposed a novel method combining DenseNet and …
Diagnosis of COVID-19 pneumonia via a novel deep learning architecture
COVID-19 is a contagious infection that has severe effects on the global economy and our
daily life. Accurate diagnosis of COVID-19 is of importance for consultants, patients, and …
daily life. Accurate diagnosis of COVID-19 is of importance for consultants, patients, and …