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 …

Deep learning models for cloud, edge, fog, and IoT computing paradigms: Survey, recent advances, and future directions

S Ahmad, I Shakeel, S Mehfuz, J Ahmad - Computer Science Review, 2023 - Elsevier
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 …

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 …

[HTML][HTML] Fake news detection: A hybrid CNN-RNN based deep learning approach

JA Nasir, OS Khan, I Varlamis - International journal of information …, 2021 - Elsevier
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 …

A survey of convolutional neural networks: analysis, applications, and prospects

Z Li, F Liu, W Yang, S Peng… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
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 …

Review of deep learning: concepts, CNN architectures, challenges, applications, future directions

L Alzubaidi, J Zhang, AJ Humaidi, A Al-Dujaili… - Journal of big Data, 2021 - Springer
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 …

Applications of convolutional neural networks for intelligent waste identification and recycling: A review

TW Wu, H Zhang, W Peng, F Lü, PJ He - Resources, Conservation and …, 2023 - Elsevier
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 …

Tissue clearing

DS Richardson, W Guan, K Matsumoto, C Pan… - Nature Reviews …, 2021 - nature.com
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 …

Deep learning for credit card fraud detection: A review of algorithms, challenges, and solutions

ID Mienye, N Jere - IEEE Access, 2024 - ieeexplore.ieee.org
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 …

DS-CNN: A pre-trained Xception model based on depth-wise separable convolutional neural network for finger vein recognition

K Shaheed, A Mao, I Qureshi, M Kumar… - Expert Systems with …, 2022 - Elsevier
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 …