Techniques and challenges of image segmentation: A review
Y Yu, C Wang, Q Fu, R Kou, F Huang, B Yang, T Yang… - Electronics, 2023 - mdpi.com
Image segmentation, which has become a research hotspot in the field of image processing
and computer vision, refers to the process of dividing an image into meaningful and non …
and computer vision, refers to the process of dividing an image into meaningful and non …
Face mask detection in smart cities using deep and transfer learning: Lessons learned from the COVID-19 pandemic
After different consecutive waves, the pandemic phase of Coronavirus disease 2019 does
not look to be ending soon for most countries across the world. To slow the spread of the …
not look to be ending soon for most countries across the world. To slow the spread of the …
Federated multi-source domain adversarial adaptation framework for machinery fault diagnosis with data privacy
Transfer learning can effectively solve the target task identification problem with the
prerequisite of sharing all user data and target data, and has become one of the most …
prerequisite of sharing all user data and target data, and has become one of the most …
Joint distribution adaptation network with adversarial learning for rolling bearing fault diagnosis
K Zhao, H Jiang, K Wang, Z Pei - Knowledge-Based Systems, 2021 - Elsevier
Numerous intelligent methods have been developed to approach the challenges of fault
diagnosis. However, due to the different distributions of training samples and test samples …
diagnosis. However, due to the different distributions of training samples and test samples …
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 …
Pseudo RGB-D face recognition
In the last decade, advances and popularity of low-cost RGB-D sensors have enabled us to
acquire depth information of objects. Consequently, researchers began to solve face …
acquire depth information of objects. Consequently, researchers began to solve face …
A novel deep learning approach for deepfake image detection
Deepfake is utilized in synthetic media to generate fake visual and audio content based on a
person's existing media. The deepfake replaces a person's face and voice with fake media …
person's existing media. The deepfake replaces a person's face and voice with fake media …
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 …