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Nov 9, 2023 · In this paper, a convolutional neural network is implemented for recognition and classification of human activity signals and digital images.
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This paper proposes an improved CNN method (EBRO-ICNN) which employs the enhanced battle royale optimization (EBRO) algorithm and proportional-derivative (PD) ...
Oct 22, 2024 · In this study, a combination of the CNN and LSTM method algorithms was applied by using several variations of the model parameter values on the ...
This paper presents an approach for image classification based on an ensemble of convolutional neural networks and the application to a real case study of ...
The model included a Parallel Convolution Scale Attention Module network (PCSAM-Net) and a Residual Convolutional Block Attention Module network (ResCBAM-Net).
Implementation of Parallel Evolutionary Convolutional Neural Network for Classification in Human Activity and Image Recognition. Chapter. Nov 2023.
In this work, we have explored the application of neuroevolution to the automatic design of CNN topolo- gies, introducing a common framework for this task and ...
Convolutional neural networks (CNNs) have demonstrated exceptional results in the analysis of time- series data when used for Human Activity Recognition ...
Mar 21, 2017 · Our paper proposes a delay synchronization convolutional neural network parallel strategy, which leverages the heterogeneous system.
Missing: Activity | Show results with:Activity
Therefore, this paper proposes an automatic human activity recognition system through deep fusion of multi-streams along with decision-level score optimization ...