wy1iu/LargeMargin_Softmax_Loss
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This project offers a specialized loss function for training neural networks to achieve more distinct and separable classification boundaries. It takes raw data inputs (like images or sensor readings) and helps produce clearer categorization and more reliable feature representations for tasks like facial recognition. It's designed for machine learning engineers and researchers aiming to improve the robustness of their classification models.
352 stars. No commits in the last 6 months.
Use this if you are training convolutional neural networks for classification or feature embedding and need to improve the model's ability to distinguish between very similar categories, especially in biometrics.
Not ideal if you are looking for a plug-and-play solution for general data analysis, as this requires integration into a neural network training pipeline.
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C++
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Last pushed
Aug 27, 2018
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