Machine and deep learning for resource allocation in multi-access edge computing: A survey
With the rapid development of Internet-of-Things (IoT) devices and mobile communication
technologies, Multi-access Edge Computing (MEC) has emerged as a promising paradigm …
technologies, Multi-access Edge Computing (MEC) has emerged as a promising paradigm …
Multiobjective Genetic Algorithm and Convolutional Neural Network Based COVID‐19 Identification in Chest X‐Ray Images
COVID‐19 is a new disease, caused by the novel coronavirus SARS‐CoV‐2, that was firstly
delineated in humans in 2019. Coronaviruses cause a range of illness in patients varying …
delineated in humans in 2019. Coronaviruses cause a range of illness in patients varying …
[PDF][PDF] Deep learning in agriculture: a review
P Bharman, SA Saad, S Khan, I Jahan… - Asian Journal of …, 2022 - researchgate.net
Deep learning (DL) is a kind of sophisticated data analysis and image processing
technology, with good results and great potential. DL has been applied to many different …
technology, with good results and great potential. DL has been applied to many different …
Automatic detection and classification of mammograms using improved extreme learning machine with deep learning
SRS Chakravarthy, H Rajaguru - Irbm, 2022 - Elsevier
Background and objective Breast cancer, the most intrusive form of cancer affecting women
globally. Next to lung cancer, breast cancer is the one that provides a greater number of …
globally. Next to lung cancer, breast cancer is the one that provides a greater number of …
Experiments of federated learning for covid-19 chest x-ray images
AI plays an important role in COVID-19 identification. Computer vision and deep learning
techniques can assist in determining COVID-19 infection with Chest X-ray Images. However …
techniques can assist in determining COVID-19 infection with Chest X-ray Images. However …
[HTML][HTML] Towards automated eye cancer classification via VGG and ResNet networks using transfer learning
DF Santos-Bustos, BM Nguyen, HE Espitia - Engineering Science and …, 2022 - Elsevier
Complex tasks such as disease diagnosis or semantic segmentation are now becoming
easier to tackle in part due to increasing advances in computing and storage. This study …
easier to tackle in part due to increasing advances in computing and storage. This study …
Experiments of federated learning for COVID-19 chest X-ray images
AI plays an important role in COVID-19 identification. Computer vision and deep learning
techniques can assist in determining COVID-19 infection with Chest X-ray Images. However …
techniques can assist in determining COVID-19 infection with Chest X-ray Images. However …
[HTML][HTML] Federated learning for the internet-of-medical-things: A survey
VK Prasad, P Bhattacharya, D Maru, S Tanwar… - Mathematics, 2022 - mdpi.com
Recently, in healthcare organizations, real-time data have been collected from connected or
implantable sensors, layered protocol stacks, lightweight communication frameworks, and …
implantable sensors, layered protocol stacks, lightweight communication frameworks, and …
A multi-task learning for cavitation detection and cavitation intensity recognition of valve acoustic signals
With the rapid development of smart manufacturing, data-driven machinery health
management has received a growing attention. As one of the most popular methods in …
management has received a growing attention. As one of the most popular methods in …
Object-independent image-based wavefront sensing approach using phase diversity images and deep learning
Q Xin, G Ju, C Zhang, S Xu - Optics express, 2019 - opg.optica.org
This paper proposes an image-based wavefront sensing approach using deep learning,
which is applicable to both point source and any extended scenes at the same time, while …
which is applicable to both point source and any extended scenes at the same time, while …