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Video surveillance using deep transfer learning and deep domain adaptation: Towards better generalization
(
Elsevier
, 2023 , Other)
Recently, developing automated video surveillance systems (VSSs) has become crucial to ensure the security and safety of the population, especially during events involving large crowds, such as sporting events. While ...
Deep learning-based middle cerebral artery blood flow abnormality detection using flow velocity waveform derived from transcranial Doppler ultrasound
(
Elsevier
, 2023 , Article)
Since the brain is unlike any other organ in that it cannot store energy and has a high metabolic demand, constant blood flow is essential for healthy brain function. The maximum flow velocity waveform that is produced by ...
NDDNet: a deep learning model for predicting neurodegenerative diseases from gait pattern
(
Springer Nature
, 2023 , Article)
Neurodegenerative diseases damage neuromuscular tissues and deteriorate motor neurons which affects the motor capacity of the patient. Particularly the walking gait is greatly influenced by the deterioration process. Early ...
Employing machine learning techniques in monitoring autocorrelated profiles
(
Springer Science and Business Media Deutschland GmbH
, 2023 , Article)
In profile monitoring, it is usually assumed that the observations between or within each profile are independent of each other. However, this assumption is often violated in manufacturing practice, and it is of utmost ...
Using artificial intelligence to improve body iron quantification: A scoping review
(
Elsevier
, 2023 , Article Review)
This scoping review explores the potential of artificial intelligence (AI) in enhancing the screening, diagnosis, and monitoring of disorders related to body iron levels. A systematic search was performed to identify studies ...
Second mesiobuccal canal segmentation with YOLOv5 architecture using cone beam computed tomography images
(
Springer
, 2023 , Article)
The objective of this study is to use a deep-learning model based on CNN architecture to detect the second mesiobuccal (MB2) canals, which are seen as a variation in maxillary molars root canals. In the current study, 922 ...
Self-ChakmaNet: A deep learning framework for indigenous language learning using handwritten characters
(
Elsevier
, 2023 , Article)
According to UNESCO's Atlas of the World's Languages in Danger, 40% of the languages today are counted as endangered in the future. Indigenous languages are endangered because of the less availability of interactive learning ...
Estimating Blood Glucose Levels Using Machine Learning Models with Non-Invasive Wearable Device Data
(
IOS Press BV
, 2023 , Conference Paper)
In 2019 alone, Diabetes Mellitus impacted 463 million individuals worldwide. Blood glucose levels (BGL) are often monitored via invasive techniques as part of routine protocols. Recently, AI-based approaches have shown the ...
AI and IoT-based concrete column base cover localization and degradation detection algorithm using deep learning techniques
(
Ain Shams University
, 2023 , Article)
Internet of Things (IoT) and Artificial Intelligence (AI) technologies are currently replacing the traditional methods of handling buildings, infrastructure, and facilities design, control, and maintenance due to their ...
Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data
(
Elsevier
, 2023 , Article)
Introduction: Diabetes Mellitus (DM) is characterized by impaired ability to metabolize glucose for use in cells for energy, resulting in high blood sugar (hyperglycemia). DM impacted 463 million individuals worldwide in ...