Nov. 16, 2023, 11:21 p.m. | /u/Ok_Ad_1034

Machine Learning

I recently implemented a [Siamese network with triplet loss](, incorporating online mining for triple selection. I'm seeking feedback on the model's performance and my code. The Flowers102 dataset was employed, aiming to determine whether two given flower images belong to the same species.

Despite achieving a 90% accuracy rate, I observed an unusual need for a low threshold (0.25) during inference. I attribute this to the inherent similarity between flower images, suggesting that a lower threshold is more appropriate. …

accuracy face flower images inference insights low machinelearning observation rate suggestions tasks threshold verification

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