Matches in SemOpenAlex for { <https://semopenalex.org/work/W4379401400> ?p ?o ?g. }
Showing items 1 to 91 of
91
with 100 items per page.
- W4379401400 endingPage "15" @default.
- W4379401400 startingPage "3" @default.
- W4379401400 abstract "Despite the intense improvements in existing architectures and the development of new deep-learning models, the core of the dense layers remains the same. Here, we are referring to the function used to process the input from the neurons of previous layers, also called the transformation function. In this study, we propose a new methodology for the computation of a neuron’s output, by adding a quadratic term to the conventional linear operation. With the aim of achieving a higher accuracy, we test the proposed process on a number of well-known data sets (MNIST, CIFAR). There is a significant improvement in the performance of a simple dense neural network. The initial accuracy itself is much higher when the new neurons are used. Initial convergence to higher accuracies is always much faster in the proposed model, and the computational time of the model is reduced to half (or even less). This enhancement can potentially be reflected in every deep learning architecture that uses a dense layer and will be remarkably higher in larger architectures that incorporate a very high number of parameters and output classes. The proposed model also fights issues like the vanishing gradient. Toward the end of the paper, we discuss the vast future scope of this study." @default.
- W4379401400 created "2023-06-06" @default.
- W4379401400 creator A5014649495 @default.
- W4379401400 creator A5085649558 @default.
- W4379401400 date "2023-01-01" @default.
- W4379401400 modified "2023-09-26" @default.
- W4379401400 title "Enhanced Dense Layers Using a Quadratic Transformation Function" @default.
- W4379401400 cites W2007339694 @default.
- W4379401400 cites W2040870580 @default.
- W4379401400 cites W2068777106 @default.
- W4379401400 cites W2194775991 @default.
- W4379401400 cites W2605622124 @default.
- W4379401400 cites W2964148965 @default.
- W4379401400 cites W2964149935 @default.
- W4379401400 cites W2964296115 @default.
- W4379401400 cites W2999571325 @default.
- W4379401400 doi "https://doi.org/10.1007/978-3-031-28324-6_1" @default.
- W4379401400 hasPublicationYear "2023" @default.
- W4379401400 type Work @default.
- W4379401400 citedByCount "0" @default.
- W4379401400 crossrefType "book-chapter" @default.
- W4379401400 hasAuthorship W4379401400A5014649495 @default.
- W4379401400 hasAuthorship W4379401400A5085649558 @default.
- W4379401400 hasConcept C104317684 @default.
- W4379401400 hasConcept C108583219 @default.
- W4379401400 hasConcept C111472728 @default.
- W4379401400 hasConcept C111919701 @default.
- W4379401400 hasConcept C11413529 @default.
- W4379401400 hasConcept C129844170 @default.
- W4379401400 hasConcept C138885662 @default.
- W4379401400 hasConcept C14036430 @default.
- W4379401400 hasConcept C154945302 @default.
- W4379401400 hasConcept C162324750 @default.
- W4379401400 hasConcept C185592680 @default.
- W4379401400 hasConcept C190502265 @default.
- W4379401400 hasConcept C204241405 @default.
- W4379401400 hasConcept C2524010 @default.
- W4379401400 hasConcept C2777303404 @default.
- W4379401400 hasConcept C2780586882 @default.
- W4379401400 hasConcept C33923547 @default.
- W4379401400 hasConcept C41008148 @default.
- W4379401400 hasConcept C45374587 @default.
- W4379401400 hasConcept C50522688 @default.
- W4379401400 hasConcept C50644808 @default.
- W4379401400 hasConcept C55493867 @default.
- W4379401400 hasConcept C78458016 @default.
- W4379401400 hasConcept C86803240 @default.
- W4379401400 hasConcept C98045186 @default.
- W4379401400 hasConceptScore W4379401400C104317684 @default.
- W4379401400 hasConceptScore W4379401400C108583219 @default.
- W4379401400 hasConceptScore W4379401400C111472728 @default.
- W4379401400 hasConceptScore W4379401400C111919701 @default.
- W4379401400 hasConceptScore W4379401400C11413529 @default.
- W4379401400 hasConceptScore W4379401400C129844170 @default.
- W4379401400 hasConceptScore W4379401400C138885662 @default.
- W4379401400 hasConceptScore W4379401400C14036430 @default.
- W4379401400 hasConceptScore W4379401400C154945302 @default.
- W4379401400 hasConceptScore W4379401400C162324750 @default.
- W4379401400 hasConceptScore W4379401400C185592680 @default.
- W4379401400 hasConceptScore W4379401400C190502265 @default.
- W4379401400 hasConceptScore W4379401400C204241405 @default.
- W4379401400 hasConceptScore W4379401400C2524010 @default.
- W4379401400 hasConceptScore W4379401400C2777303404 @default.
- W4379401400 hasConceptScore W4379401400C2780586882 @default.
- W4379401400 hasConceptScore W4379401400C33923547 @default.
- W4379401400 hasConceptScore W4379401400C41008148 @default.
- W4379401400 hasConceptScore W4379401400C45374587 @default.
- W4379401400 hasConceptScore W4379401400C50522688 @default.
- W4379401400 hasConceptScore W4379401400C50644808 @default.
- W4379401400 hasConceptScore W4379401400C55493867 @default.
- W4379401400 hasConceptScore W4379401400C78458016 @default.
- W4379401400 hasConceptScore W4379401400C86803240 @default.
- W4379401400 hasConceptScore W4379401400C98045186 @default.
- W4379401400 hasLocation W43794014001 @default.
- W4379401400 hasOpenAccess W4379401400 @default.
- W4379401400 hasPrimaryLocation W43794014001 @default.
- W4379401400 hasRelatedWork W2167735388 @default.
- W4379401400 hasRelatedWork W2276478028 @default.
- W4379401400 hasRelatedWork W2904174853 @default.
- W4379401400 hasRelatedWork W2908596665 @default.
- W4379401400 hasRelatedWork W2947175736 @default.
- W4379401400 hasRelatedWork W3156786002 @default.
- W4379401400 hasRelatedWork W3177008965 @default.
- W4379401400 hasRelatedWork W4287510235 @default.
- W4379401400 hasRelatedWork W4309224979 @default.
- W4379401400 hasRelatedWork W2247596074 @default.
- W4379401400 isParatext "false" @default.
- W4379401400 isRetracted "false" @default.
- W4379401400 workType "book-chapter" @default.