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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 ...
Data-driven fault detection and isolation of nonlinear systems using deep learning for Koopman operator
(
ISA - Instrumentation, Systems, and Automation Society
, 2023 , Article)
This paper proposes a data-driven actuator fault detection and isolation approach for the general class of nonlinear systems. The proposed method uses a deep neural network architecture to obtain an invariant set of basis ...
Toward an NLP Approach for Transforming Paper Contracts into Smart Contracts
(
Springer Science and Business Media Deutschland GmbH
, 2023 , Conference Paper)
Identifying and extracting information from contracts is an important task of contract analysis, which is mostly performed manually by lawyers and legal specialists. This manual analysis is a time-consuming, error-prone ...
DSPNet: A Self-ONN Model for Robust DSPN Diagnosis From Temperature Maps
(
Institute of Electrical and Electronics Engineers Inc.
, 2023 , Article)
Diabetic sensorimotor polyneuropathy (DSPN) leads to pain, diabetic foot ulceration (DFU), amputation, and death. The diagnosis of advanced DSPN to identify those at risk is key to preventing DFU and amputation. Alterations ...
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 ...
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 ...
Exploiting Spatial Correlations: Group Key Generation for Secure IoT Device Networks
(
Institute of Electrical and Electronics Engineers Inc.
, 2023 , Conference Paper)
With the exponential growth in IoT devices, especially in healthcare systems, where multiple devices are attributed to one person, the need for a secure and effective group secret key (GSK) generation is intrinsic. GSKs ...
Deep Learning-Based Conjunctival Melanoma Detection Using Ocular Surface Images
(
springer link
, 2023 , Article)
The human eye could be affected with conjunctival melanoma, which indicates a fatal malignant growth of the eye. Being a very rare disease, there exists a lack of related data in the literature. Also, very few studies ...