A Study on the effects of recursive convolutional layers in ...
www.sciencedirect.com › article › pii
Oct 14, 2021 · This paper presents a new model of convolutional neural networks (CNN) which features fully recursive convolutional layers (RCLs).
Jul 28, 2024 · The Recursive Convolutional Layer (RCL) is a module that wraps a recursive feedback loop around a convolutional layer (CL).
Jul 18, 2024 · The RCL has been proposed to address some of the shortcomings of Convolutional Neural Networks (CNNs), as its unfolding increases the depth of a ...
Aug 11, 2023 · Additionally, our findings demonstrate that RCLs are able to efficiently simulate an increase of depth and to learn weights of greater diversity ...
Missing: Study | Show results with:Study
To overcome problems with the design of large networks, particularly with respect to the depth of the network, this paper presents a new model of ...
Highlights •Developing a new recursive convolutional layer (RCL) able to stop the iteration when the hidden state stabilize.•First network to have different ...
The Recursive Convolutional Layer (RCL) is a module that wraps a recursive feedback loop around a convolutional layer (CL). The RCL has been proposed to address ...
Missing: Study | Show results with:Study
Jun 30, 2023 · The FRPN differs in that there is a single hidden layer, whose neurons are inter-connected to all neurons in the layer including to ...
Convolutional layers in CNN extract features. Increasing convolutional layers can enhance model performance, especially in shallow CNNs, as shown by the study ...
On the effects of recursive convolutional layers in convolutional ...
colab.ws › j.neucom.2024.127767
We conclude that the replacement of CLs by RCLs shows great potential in designing high-performance shallow CNNs. References 33.