Review of deep learning: concepts, CNN architectures, challenges, applications, future directions
In the last few years, the deep learning (DL) computing paradigm has been deemed the
Gold Standard in the machine learning (ML) community. Moreover, it has gradually become …
Gold Standard in the machine learning (ML) community. Moreover, it has gradually become …
Personalized human activity recognition based on integrated wearable sensor and transfer learning
Human activity recognition (HAR) based on the wearable device has attracted more
attention from researchers with sensor technology development in recent years. However …
attention from researchers with sensor technology development in recent years. However …
Privacy-preserving cross-environment human activity recognition
Recent studies have demonstrated the success of using the channel state information (CSI)
from the WiFi signal to analyze human activities in a fixed and well-controlled environment …
from the WiFi signal to analyze human activities in a fixed and well-controlled environment …
[HTML][HTML] Conflux LSTMs network: A novel approach for multi-view action recognition
Multi-view action recognition (MVAR) is an optimal technique to acquire numerous clues
from different views data for effective action recognition, however, it is not well explored yet …
from different views data for effective action recognition, however, it is not well explored yet …
Evidential reasoning with hesitant fuzzy belief structures for human activity recognition
In the original belief function (BF) theory, a precise-valued belief structure has been widely
used to represent uncertain information. However, this mentioned belief structure is difficult …
used to represent uncertain information. However, this mentioned belief structure is difficult …
Medisecfed: Private and secure medical image classification in the presence of malicious clients
Deep learning demonstrates its efficacy and potential to solve challenging computer vision
problems in medical and other industrial applications. Federated learning is a learning …
problems in medical and other industrial applications. Federated learning is a learning …
Physique-based human activity recognition using ensemble learning and smartphone sensors
Traditional methods of Human Activity Recognition (HAR) do not take into consideration
physical attributes of human subjects such as height, weight, gender etc. Thus, a particular …
physical attributes of human subjects such as height, weight, gender etc. Thus, a particular …
Bridge health anomaly detection using deep support vector data description
JX Yang, F Yang, L Zhang, R Li, S Jiang, G Wang… - Neurocomputing, 2021 - Elsevier
As an extremely important part of traffic arteries, bridge structure plays an essential role in
national economic construction, social development and smart city. Thus the monitoring of …
national economic construction, social development and smart city. Thus the monitoring of …
Petersen graph multi-orientation based multi-scale ternary pattern (PGMO-MSTP): an efficient descriptor for texture and material recognition
Classifying and modeling texture images, especially those with significant rotation,
illumination, scale, and view-point variations, is a hot topic in the computer vision field …
illumination, scale, and view-point variations, is a hot topic in the computer vision field …
Using graph representation learning to predict salivary cortisol levels in pancreatic cancer patients
Cortisol is a glucocorticoid hormone that is critical to immune system functioning. Studies
show that prolonged exposure to high levels of cortisol can lead to a range of physical …
show that prolonged exposure to high levels of cortisol can lead to a range of physical …