Dynamical activation of function in metalloenzymes
Sign Up to like & getrecommendations! Published in 2022 at "FEBS Letters"
DOI: 10.1002/1873-3468.14515
Abstract: Formulations of hydrogen tunneling in enzyme‐catalysed C–H activation reactions indicate enthalpic barriers to reaction that are independent of chemical steps and dependent on the protein scaffold. A tool to identify catalytically relevant site‐specific protein thermal… read more here.
Keywords: activation function; thermal networks; function metalloenzymes; protein ... See more keywords
Early breast cancer diagnosis using cogent activation function‐based deep learning implementation on screened mammograms
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Imaging Systems and Technology"
DOI: 10.1002/ima.22701
Abstract: Breast cancer is detected in one out of eight females worldwide. Principally biomedical image processing techniques work with images captured by a microscope and then analyzed with the help of different algorithms and methods. Instead… read more here.
Keywords: diagnosis; breast cancer; activation function;
Construction of feedforward neural networks with simple architectures and approximation abilities
Sign Up to like & getrecommendations! Published in 2020 at "Mathematical Methods in the Applied Sciences"
DOI: 10.1002/mma.6876
Abstract: The universal approximation property of feedforward neural networks (FNNs) is the basis for all FNNs applications. In almost all existing FNN approximation studies, it is always assumed that the activation function of the network satisfies… read more here.
Keywords: feedforward neural; neural networks; activation function; function ... See more keywords
Data density-based clustering for regularized fuzzy neural networks based on nullneurons and robust activation function
Sign Up to like & getrecommendations! Published in 2019 at "Soft Computing"
DOI: 10.1007/s00500-019-03792-z
Abstract: This paper proposes the use of fuzzification functions based on clustering of data based on their density to perform the granularization of the input space. The neurons formed in this layer are built through the… read more here.
Keywords: based clustering; layer; activation function; density ... See more keywords
Antagonist-perturbation mechanism for activation function-2 fixed motifs: active conformation and docking mode of retinoid X receptor antagonists
Sign Up to like & getrecommendations! Published in 2017 at "Journal of Computer-Aided Molecular Design"
DOI: 10.1007/s10822-017-0025-6
Abstract: HX531, which contains a dibenzodiazepine skeleton, is one of the first retinoid X receptor (RXR) antagonists. Functioning via RXR-PPARγ heterodimer, this compound is receiving a lot of attention as a therapeutic drug candidate for diabetic… read more here.
Keywords: function fixed; docking mode; active conformation; retinoid receptor ... See more keywords
A framework for automatic detection of heart diseases using dynamic deep neural activation functions
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Ambient Intelligence and Humanized Computing"
DOI: 10.1007/s12652-020-01883-6
Abstract: Availability of the information related to the medical tests are wide and thus the demand for advanced analysis is continuously growing. In the recent past, a number of automatic disease detection algorithms are generated. The… read more here.
Keywords: detection; disease; activation functions; activation ... See more keywords
Hyperbolic Hopfield neural networks with directional multistate activation function
Sign Up to like & getrecommendations! Published in 2018 at "Neurocomputing"
DOI: 10.1016/j.neucom.2017.10.053
Abstract: Abstract Complex-valued Hopfield neural networks (CHNNs) have been applied to various fields, although they tend to suffer from low noise tolerance. Rotational invariance, which is an inherent property of CHNNs, reduces noise tolerance. CHNNs have… read more here.
Keywords: multistate activation; neural networks; noise tolerance; hopfield neural ... See more keywords
RMAF: Relu-Memristor-Like Activation Function for Deep Learning
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.2987829
Abstract: Activation functions facilitate deep neural networks by introducing non-linearity to the learning process. The non-linearity feature gives the neural network the ability to learn complex patterns. Recently, the most widely used activation function is the… read more here.
Keywords: activation; rmaf; activation function; relu ... See more keywords
Triple-Sigmoid Activation Function for Deep Open-Set Recognition
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3192621
Abstract: Traditional models for various machine learning problems such as image classification perform well only under the assumption of a closed set. This implies that inputs must belong to the classes for which the models were… read more here.
Keywords: triple sigmoid; activation function; model; set recognition ... See more keywords
Fisher Information Matrix and its Application of Bipolar Activation Function Based Multilayer Perceptrons With General Gaussian Input
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3227427
Abstract: For the widely used multilayer perceptrons (MLPs), there exist singularities in the parameter space where Fisher information matrix (FIM) degenerates on these subspaces. The singularities seriously influence the learning dynamics of MLPs which have attracted… read more here.
Keywords: activation function; information matrix; function; fisher information ... See more keywords
Attention-Based Convolutional Neural Network for Pavement Crack Detection
Sign Up to like & getrecommendations! Published in 2021 at "Advances in Materials Science and Engineering"
DOI: 10.1155/2021/5520515
Abstract: Achieving high detection accuracy of pavement cracks with complex textures under different lighting conditions is still challenging. In this context, an encoder-decoder network-based architecture named CrackResAttentionNet was proposed in this study, and the position attention… read more here.
Keywords: detection; bce loss; attention; prelu activation ... See more keywords