Demystifying the role of natural language processing (NLP) in smart city applications: background, motivation, recent advances, and future research directions
Smart cities provide an efficient infrastructure for the enhancement of the quality of life of the
people by aiding in fast urbanization and resource management through sustainable and …
people by aiding in fast urbanization and resource management through sustainable and …
A survey of machine learning-based methods for COVID-19 medical image analysis
K Sailunaz, T Özyer, J Rokne, R Alhajj - Medical & Biological Engineering …, 2023 - Springer
The ongoing COVID-19 pandemic caused by the SARS-CoV-2 virus has already resulted in
6.6 million deaths with more than 637 million people infected after only 30 months since the …
6.6 million deaths with more than 637 million people infected after only 30 months since the …
Faster Mean-shift: GPU-accelerated clustering for cosine embedding-based cell segmentation and tracking
Recently, single-stage embedding based deep learning algorithms gain increasing attention
in cell segmentation and tracking. Compared with the traditional “segment-then-associate” …
in cell segmentation and tracking. Compared with the traditional “segment-then-associate” …
DL-PR: Generalized automatic modulation classification method based on deep learning with priori regularization
Q Zheng, X Tian, Z Yu, H Wang, A Elhanashi… - … Applications of Artificial …, 2023 - Elsevier
Automatic modulation classification (AMC) is an essential and indispensable topic in the
development of cognitive radios. It is the cornerstone of adaptive modulation and …
development of cognitive radios. It is the cornerstone of adaptive modulation and …
Insulator-defect detection algorithm based on improved YOLOv7
J Zheng, H Wu, H Zhang, Z Wang, W Xu - Sensors, 2022 - mdpi.com
Existing detection methods face a huge challenge in identifying insulators with minor defects
when targeting transmission line images with complex backgrounds. To ensure the safe …
when targeting transmission line images with complex backgrounds. To ensure the safe …
GPU-accelerated Faster Mean Shift with euclidean distance metrics
Handling clustering problems are important in data statistics, pattern recognition and image
processing. The mean-shift algorithm, a common unsupervised algorithms, is widely used to …
processing. The mean-shift algorithm, a common unsupervised algorithms, is widely used to …
Application of wavelet-packet transform driven deep learning method in PM2. 5 concentration prediction: A case study of Qingdao, China
Q Zheng, X Tian, Z Yu, N Jiang, A Elhanashi… - Sustainable Cities and …, 2023 - Elsevier
Air pollution is one of the most serious environmental problems faced by human beings, and
it is also a hot topic in the development of sustainable cities. Accurate PM 2.5 prediction …
it is also a hot topic in the development of sustainable cities. Accurate PM 2.5 prediction …
VoxelEmbed: 3D instance segmentation and tracking with voxel embedding based deep learning
Recent advances in bioimaging have provided scientists a superior high spatial-temporal
resolution to observe dynamics of living cells as 3D volumetric videos. Unfortunately, the 3D …
resolution to observe dynamics of living cells as 3D volumetric videos. Unfortunately, the 3D …
Class-aware fish species recognition using deep learning for an imbalanced dataset
Fish species recognition is crucial to identifying the abundance of fish species in a specific
area, controlling production management, and monitoring the ecosystem, especially …
area, controlling production management, and monitoring the ecosystem, especially …
Computer vision and machine learning-based gait pattern recognition for flat fall prediction
Background: Gait recognition has been applied in the prediction of the probability of elderly
flat ground fall, functional evaluation during rehabilitation, and the training of patients with …
flat ground fall, functional evaluation during rehabilitation, and the training of patients with …