crosslayer hybrid activation functions relu and  (SoftMax Inc)

Journal: Scientific Reports

Article Title: Imbalanced graph learning via mixed entropy minimization

doi: 10.1038/s41598-024-75999-6

Figure Lengend Snippet: Summary of notations with definitions.

Article Snippet: \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\sigma$$\end{document} σ , Activation function ReLU , \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\widetilde{G}$$\end{document} G ~ , Enhanced graph.

Techniques: Plasmid Preparation, Activation Assay

Journal: Sensors (Basel, Switzerland)

Article Title: Exploring Convolutional Neural Network Architectures for EEG Feature Extraction

doi: 10.3390/s24030877

Figure Lengend Snippet: Applying CNN to Feature Extraction from EEG Signals.

Article Snippet: Different activation functions are employed in fully connected layers (FC), with the Rectified Linear Unit (ReLU) activation function being a common choice for neural network layers, especially for tasks in the frequency domain and spatial problem-solving, such as those addressed by Softmax.

Techniques: Extraction, Activation Assay, Biomarker Discovery, Blocking Assay, Sampling, Modification

Journal: Sensors (Basel, Switzerland)

Article Title: Soil-MobiNet: A Convolutional Neural Network Model Base Soil Classification to Determine Soil Morphology and Its Geospatial Location

doi: 10.3390/s23156709

Figure Lengend Snippet: Values of the Parameters in the Proposed Soil-MobiNet Architecture.

Article Snippet: Image Size , 224 × 224 , Activation function , ReLu Softmax , Avg. Epoch time , 108 s.

Techniques: Software, Activation Assay