This figure shows the accuracy and loss curves generated during the training process. We trained different neural networks on the CIFAR-100 dataset. For each network, the same training strategy was applied to every image in the dataset. The blue curve represents the accuracy after replacing the convolution layers, which achieves a higher accuracy compared to other networks.In the figure, the green curve represents the network after replacing standard convolution with the SCT module.

Dataset Files

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[1] shaohui pan, "Datasets of Spatial and Channel Two-step Processing Lightweight Modules", IEEE Dataport, 2024. [Online]. Available: http://dx.doi.org/10.21227/9562-jk23. Accessed: Dec. 05, 2024.
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url = {http://dx.doi.org/10.21227/9562-jk23},
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title = {Datasets of Spatial and Channel Two-step Processing Lightweight Modules},
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shaohui pan. (2024). Datasets of Spatial and Channel Two-step Processing Lightweight Modules. IEEE Dataport. http://dx.doi.org/10.21227/9562-jk23
shaohui pan, 2024. Datasets of Spatial and Channel Two-step Processing Lightweight Modules. Available at: http://dx.doi.org/10.21227/9562-jk23.
shaohui pan. (2024). "Datasets of Spatial and Channel Two-step Processing Lightweight Modules." Web.
1. shaohui pan. Datasets of Spatial and Channel Two-step Processing Lightweight Modules [Internet]. IEEE Dataport; 2024. Available from : http://dx.doi.org/10.21227/9562-jk23
shaohui pan. "Datasets of Spatial and Channel Two-step Processing Lightweight Modules." doi: 10.21227/9562-jk23