Big data and machine learning algorithms for health-care delivery
KY Ngiam, W Khor - The Lancet Oncology, 2019 - thelancet.com
Analysis of big data by machine learning offers considerable advantages for assimilation
and evaluation of large amounts of complex health-care data. However, to effectively use …
and evaluation of large amounts of complex health-care data. However, to effectively use …
[HTML][HTML] Green learning: Introduction, examples and outlook
CCJ Kuo, AM Madni - Journal of Visual Communication and Image …, 2023 - Elsevier
Rapid advances in artificial intelligence (AI) in the last decade have been largely built upon
the wide applications of deep learning (DL). However, the high carbon footprint yielded by …
the wide applications of deep learning (DL). However, the high carbon footprint yielded by …
Streamflow prediction using an integrated methodology based on convolutional neural network and long short-term memory networks
Streamflow (Q flow) prediction is one of the essential steps for the reliable and robust water
resources planning and management. It is highly vital for hydropower operation, agricultural …
resources planning and management. It is highly vital for hydropower operation, agricultural …
[HTML][HTML] Intelligent waste management system using deep learning with IoT
Waste management leads to the demolition of waste conducted by recycling and landfilling.
Deep learning and the Internet of things (IoT) confer an agile solution in classification and …
Deep learning and the Internet of things (IoT) confer an agile solution in classification and …
Wind speed prediction of unmanned sailboat based on CNN and LSTM hybrid neural network
Z Shen, X Fan, L Zhang, H Yu - Ocean Engineering, 2022 - Elsevier
Wind speed is a key factor for unmanned sailboats, and accurate prediction of wind speed is
of great significance to the safety and performance of unmanned sailboats. In this study, a …
of great significance to the safety and performance of unmanned sailboats. In this study, a …
[HTML][HTML] Capsule networks–a survey
Modern day computer vision tasks requires efficient solution to problems such as image
recognition, natural language processing, object detection, object segmentation and …
recognition, natural language processing, object detection, object segmentation and …
Graph representation learning: a survey
Research on graph representation learning has received great attention in recent years
since most data in real-world applications come in the form of graphs. High-dimensional …
since most data in real-world applications come in the form of graphs. High-dimensional …
Performance analysis of deep learning algorithms in diagnosis of malaria disease
Malaria is predominant in many subtropical nations with little health-monitoring
infrastructure. To forecast malaria and condense the disease's impact on the population …
infrastructure. To forecast malaria and condense the disease's impact on the population …
Data augmentation and transfer learning for brain tumor detection in magnetic resonance imaging
A Anaya-Isaza, L Mera-Jiménez - IEEE Access, 2022 - ieeexplore.ieee.org
The exponential growth of deep learning networks has allowed us to tackle complex tasks,
even in fields as complicated as medicine. However, using these models requires a large …
even in fields as complicated as medicine. However, using these models requires a large …
VGGCOV19-NET: automatic detection of COVID-19 cases from X-ray images using modified VGG19 CNN architecture and YOLO algorithm
A Karacı - Neural Computing and Applications, 2022 - Springer
X-ray images are an easily accessible, fast, and inexpensive method of diagnosing COVID-
19, widely used in health centers around the world. In places where there is a shortage of …
19, widely used in health centers around the world. In places where there is a shortage of …