A dual-channel attention metric learning model with Circle Loss and hard sample mining matches single neurons across two-photon and fMOST images using only 190 training pairs, claiming 77.4% recall at 90.1% specificity.
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A Few-Shot Metric Learning Method with Dual-Channel Attention for Cross-Modal Same-Neuron Identification
A dual-channel attention metric learning model with Circle Loss and hard sample mining matches single neurons across two-photon and fMOST images using only 190 training pairs, claiming 77.4% recall at 90.1% specificity.