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Theoretical understanding of convolutional neural network: Concepts, architectures, applications, future directions
MM Taye - Computation, 2023 - mdpi.com
Convolutional neural networks (CNNs) are one of the main types of neural networks used for
image recognition and classification. CNNs have several uses, some of which are object …
image recognition and classification. CNNs have several uses, some of which are object …
Deep learning models for cloud, edge, fog, and IoT computing paradigms: Survey, recent advances, and future directions
In recent times, the machine learning (ML) community has recognized the deep learning
(DL) computing model as the Gold Standard. DL has gradually become the most widely …
(DL) computing model as the Gold Standard. DL has gradually become the most widely …
Review and empirical analysis of sparrow search algorithm
Y Yue, L Cao, D Lu, Z Hu, M Xu, S Wang, B Li… - Artificial Intelligence …, 2023 - Springer
In recent years, swarm intelligence algorithms have received extensive attention and
research. Swarm intelligence algorithms are a biological heuristic method, which is widely …
research. Swarm intelligence algorithms are a biological heuristic method, which is widely …
[HTML][HTML] Fake news detection: A hybrid CNN-RNN based deep learning approach
The explosion of social media allowed individuals to spread information without cost, with
little investigation and fewer filters than before. This amplified the old problem of fake news …
little investigation and fewer filters than before. This amplified the old problem of fake news …
A survey of convolutional neural networks: analysis, applications, and prospects
A convolutional neural network (CNN) is one of the most significant networks in the deep
learning field. Since CNN made impressive achievements in many areas, including but not …
learning field. Since CNN made impressive achievements in many areas, including but not …
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 …
Applications of convolutional neural networks for intelligent waste identification and recycling: A review
With the implementations of “Zero Waste” and Industry 4.0, the rapidly increasing
applications of artificial intelligence in waste management have generated a large amount of …
applications of artificial intelligence in waste management have generated a large amount of …
Tissue clearing
Tissue clearing of gross anatomical samples was first described more than a century ago
and has only recently found widespread use in the field of microscopy. This renaissance has …
and has only recently found widespread use in the field of microscopy. This renaissance has …
Deep learning for credit card fraud detection: A review of algorithms, challenges, and solutions
Deep learning (DL), a branch of machine learning (ML), is the core technology in today's
technological advancements and innovations. Deep learning-based approaches are the …
technological advancements and innovations. Deep learning-based approaches are the …
DS-CNN: A pre-trained Xception model based on depth-wise separable convolutional neural network for finger vein recognition
Finger vein recognition received special attention among all other biometric traits due to its
high security. Adequate recognition and classification accuracy ensure the security of …
high security. Adequate recognition and classification accuracy ensure the security of …