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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 ...
WSNet - Convolutional Neural Networkbased Word Spotting for Arabic and English Handwritten Documents
(
UIKTEN - Association for Information Communication Technology Education and Science
, 2022 , Article)
This paper proposes a new convolutional neural network architecture to tackle the problem of word spotting in handwritten documents. A Deep learning approach using a novel Convolutional Neural Network is developed for the ...
Uncertainty awareness in transmission line fault analysis: A deep learning based approach
(
Elsevier Ltd
, 2022 , Article)
With the expansion of the modern power system, it is of increasing significance to analyze the faults in the transmission lines. As the transmission line is the most exposed element of a power system, it is prone to different ...
A comparative analysis to forecast carbon dioxide emissions
(
Elsevier Ltd
, 2022 , Article)
Despite the growing knowledge and commitment to climate change, carbon dioxide (CO2) emissions continue to rise dramatically throughout the planet. In recent years, the consequences of climate change have become more ...
Investigating 3D holoscopic visual content upsampling using super-resolution for cultural heritage digitization
(
Elsevier B.V.
, 2019 , Article)
Through this paper, we aim at investigating the impact of using deep learning-based technologies such as super-resolution on Holoscopic 3D (H3D) images. Holoscopic 3D imaging is a technology that aims at providing ...
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 ...
A machine learning framework for enhancing digital experiences in cultural heritage
(
Emerald Group Publishing Ltd.
, 2020 , Article)
Purpose: Digital tools have been used to document cultural heritage with high-quality imaging and metadata. However, some of the historical assets are totally or partially unlabeled and some are physically damaged, which ...
CNN Features vs Classical Features for Largescale Cultural Image Retrieval
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
Modern applications for cultural content enrichment and management require low delay image retrieval methods in large databases. Classical image retrieval methods are suitable for certain applications but are also known ...
Investigating low-delay deep learning-based cultural image reconstruction
(
Springer Science and Business Media Deutschland GmbH
, 2020 , Conference Paper)
Numerous cultural assets host a great historical and moral value, but due to their degradation, this value is heavily affected as their attractiveness is lost. One of the solutions that most heritage organizations and ...
The research on detection of crop diseases ranking based on transfer learning
(
Institute of Electrical and Electronics Engineers Inc.
, 2019 , Conference Paper)
Crop diseases are a major global threat to food security. Because the lack of agriculture experts or necessary facilities, it is difficult to determine the type of disease, as well as the degree of disease in time, which ...