Artificial intelligence in visible light positioning for indoor IoT: A methodological review
Indoor communication and positioning are significant fields of applications for indoor Internet
of Things (IoT) given the rapid growth of IoT in smart cities, smart grids, and smart industries …
of Things (IoT) given the rapid growth of IoT in smart cities, smart grids, and smart industries …
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 …
A fast granular-ball-based density peaks clustering algorithm for large-scale data
D Cheng, Y Li, S **a, G Wang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Density peaks clustering algorithm (DP) has difficulty in clustering large-scale data, because
it requires the distance matrix to compute the density and-distance for each object, which …
it requires the distance matrix to compute the density and-distance for each object, which …
BANet: A balance attention network for anchor-free ship detection in SAR images
Q Hu, S Hu, S Liu - IEEE Transactions on Geoscience and …, 2022 - ieeexplore.ieee.org
Recently, methods based on deep learning have been successfully applied to ship detection
for synthetic aperture radar (SAR) images. However, most current ship detection networks …
for synthetic aperture radar (SAR) images. However, most current ship detection networks …
MRDDANet: A multiscale residual dense dual attention network for SAR image denoising
Synthetic aperture radar (SAR), due to its inherent characteristics, will produce speckle
noise, which results in the deterioration of image quality, so the removal of speckle in SAR …
noise, which results in the deterioration of image quality, so the removal of speckle in SAR …
Machine Learning in Solid‐State Hydrogen Storage Materials: Challenges and Perspectives
Abstract Machine learning (ML) has emerged as a pioneering tool in advancing the research
application of high‐performance solid‐state hydrogen storage materials (HSMs). This review …
application of high‐performance solid‐state hydrogen storage materials (HSMs). This review …
Subject-independent emotion recognition of EEG signals based on dynamic empirical convolutional neural network
S Liu, X Wang, L Zhao, J Zhao, Q **n… - … /ACM transactions on …, 2020 - ieeexplore.ieee.org
Affective computing is one of the key technologies to achieve advanced brain-machine
interfacing. It is increasingly concerning research orientation in the field of artificial …
interfacing. It is increasingly concerning research orientation in the field of artificial …
K-DBSCAN: An improved DBSCAN algorithm for big data
N Gholizadeh, H Saadatfar, N Hanafi - The Journal of supercomputing, 2021 - Springer
Big data storage and processing are among the most important challenges now. Among
data mining algorithms, DBSCAN is a common clustering method. One of the most important …
data mining algorithms, DBSCAN is a common clustering method. One of the most important …
An improved DBSCAN algorithm based on the neighbor similarity and fast nearest neighbor query
SS Li - Ieee Access, 2020 - ieeexplore.ieee.org
DBSCAN is the most famous density based clustering algorithm which is one of the main
clustering paradigms. However, there are many redundant distance computations among …
clustering paradigms. However, there are many redundant distance computations among …
K-means clustering with natural density peaks for discovering arbitrary-shaped clusters
D Cheng, J Huang, S Zhang, S **a… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Due to simplicity, K-means has become a widely used clustering method. However, its
clustering result is seriously affected by the initial centers and the allocation strategy makes …
clustering result is seriously affected by the initial centers and the allocation strategy makes …