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Multi-sensor information fusion based on machine learning for real applications in human activity recognition: State-of-the-art and research challenges
This paper firstly introduces common wearable sensors, smart wearable devices and the key
application areas. Since multi-sensor is defined by the presence of more than one model or …
application areas. Since multi-sensor is defined by the presence of more than one model or …
Multi-user activity recognition: Challenges and opportunities
Human activity recognition has attracted enormous research interest thanks to its
fundamental importance in several domains spanning from health-care to security, safety …
fundamental importance in several domains spanning from health-care to security, safety …
[HTML][HTML] Insights into Internet of Medical Things (IoMT): Data fusion, security issues and potential solutions
Abstract The Internet of Medical Things (IoMT) has created a wide range of opportunities for
knowledge exchange in numerous industries. The opportunities include patient …
knowledge exchange in numerous industries. The opportunities include patient …
A survey on deep learning in medicine: Why, how and when?
New technologies are transforming medicine, and this revolution starts with data. Health
data, clinical images, genome sequences, data on prescribed therapies and results …
data, clinical images, genome sequences, data on prescribed therapies and results …
Real-time detection of apple leaf diseases using deep learning approach based on improved convolutional neural networks
P Jiang, Y Chen, B Liu, D He, C Liang - Ieee Access, 2019 - ieeexplore.ieee.org
Alternaria leaf spot, Brown spot, Mosaic, Grey spot, and Rust are five common types of apple
leaf diseases that severely affect apple yield. However, the existing research lacks an …
leaf diseases that severely affect apple yield. However, the existing research lacks an …
PMRSS: Privacy-Preserving Medical Record Searching Scheme for Intelligent Diagnosis in IoT Healthcare
Y Sun, J Liu, K Yu, M Alazab… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
In medical field, previous patients' cases are extremely private as well as intensely valuable
to current disease diagnosis. Therefore, how to make full use of precious cases while not …
to current disease diagnosis. Therefore, how to make full use of precious cases while not …
COVID-19 classification by CCSHNet with deep fusion using transfer learning and discriminant correlation analysis
Aim: COVID-19 is a disease caused by a new strain of coronavirus. Up to 18th October
2020, worldwide there have been 39.6 million confirmed cases resulting in more than 1.1 …
2020, worldwide there have been 39.6 million confirmed cases resulting in more than 1.1 …
Deep learning for prediction of depressive symptoms in a large textual dataset
Depression is a common illness worldwide with potentially severe implications. Early
identification of depressive symptoms is a crucial first step towards assessment, intervention …
identification of depressive symptoms is a crucial first step towards assessment, intervention …
Risk prediction of diabetes: big data mining with fusion of multifarious physical examination indicators
H Yang, Y Luo, X Ren, M Wu, X He, B Peng, K Deng… - Information …, 2021 - Elsevier
Diabetes is a global epidemic. Long-term exposure to hyperglycemia can cause chronic
damage to various tissues. Thus, early diagnosis of diabetes is crucial. In this study, we …
damage to various tissues. Thus, early diagnosis of diabetes is crucial. In this study, we …
Grape leaf disease identification using improved deep convolutional neural networks
B Liu, Z Ding, L Tian, D He, S Li, H Wang - Frontiers in plant science, 2020 - frontiersin.org
Anthracnose, brown spot, mites, black rot, downy mildew, and leaf blight are six common
grape leaf pests and diseases, which cause severe economic losses to the grape industry …
grape leaf pests and diseases, which cause severe economic losses to the grape industry …