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What is Stad 854 about?

This study introduces a multiscale convolutional capsule network (MSCCN) for galaxy morphology classification, addressing limitations in existing deep learning methods. The MSCCN model achieves high accuracy (97%), precision (96%), recall (98%), and F1-score (97%) by utilizing a multibranch structure for feature extraction and replacing the softmax function with a sigmoid function for improved robustness. The results demonstrate the model

Author

ogochalomon1111

Language

EN