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Activation functions in deep learning: A comprehensive survey and benchmark
Neural networks have shown tremendous growth in recent years to solve numerous
problems. Various types of neural networks have been introduced to deal with different types …
problems. Various types of neural networks have been introduced to deal with different types …
[HTML][HTML] Recurrent neural networks: A comprehensive review of architectures, variants, and applications
Recurrent neural networks (RNNs) have significantly advanced the field of machine learning
(ML) by enabling the effective processing of sequential data. This paper provides a …
(ML) by enabling the effective processing of sequential data. This paper provides a …
Activation functions: Comparison of trends in practice and research for deep learning
Deep neural networks have been successfully used in diverse emerging domains to solve
real world complex problems with may more deep learning (DL) architectures, being …
real world complex problems with may more deep learning (DL) architectures, being …
Deep reinforcement learning assisted federated learning algorithm for data management of IIoT
The continuous expanded scale of the industrial Internet of Things (IIoT) leads to IIoT
equipments generating massive amounts of user data every moment. According to the …
equipments generating massive amounts of user data every moment. According to the …
Induction motor fault diagnosis using support vector machine, neural networks, and boosting methods
Induction motors are robust and cost effective; thus, they are commonly used as power
sources in various industrial applications. However, due to the characteristics of induction …
sources in various industrial applications. However, due to the characteristics of induction …
A novel malware classification and augmentation model based on convolutional neural network
The rapid development and widespread use of the Internet have led to an increase in the
number and variety of malware proliferating via the Internet. Malware is the general …
number and variety of malware proliferating via the Internet. Malware is the general …
Three decades of activations: A comprehensive survey of 400 activation functions for neural networks
Neural networks have proven to be a highly effective tool for solving complex problems in
many areas of life. Recently, their importance and practical usability have further been …
many areas of life. Recently, their importance and practical usability have further been …
PKRT-Net: Prior knowledge-based relation transformer network for optic cup and disc segmentation
Glaucoma causes irreversible vision loss, and early detection of glaucoma is essential to
protect the vision of patients. The optic cup (OC) and optic disc (OD) are two critical …
protect the vision of patients. The optic cup (OC) and optic disc (OD) are two critical …
[HTML][HTML] Formwork pressure prediction in cast-in-place self-compacting concrete using deep learning
The prediction of formwork pressure exerted by self-compacting concrete (SCC) remains a
challenge not only to researchers but also to engineers and contractors on the construction …
challenge not only to researchers but also to engineers and contractors on the construction …
A hybrid supervised machine learning classifier system for breast cancer prognosis using feature selection and data imbalance handling approaches
Nowadays, breast cancer is the most frequent cancer among women. Early detection is a
critical issue that can be effectively achieved by machine learning (ML) techniques. Thus in …
critical issue that can be effectively achieved by machine learning (ML) techniques. Thus in …