IonMorphNet is a ConvNeXt-based classifier trained on six spatial pattern classes from 53 MSI datasets that performs generalizable peak picking and improves mSCF1 by 7% over prior methods while also aiding tumor classification via ion selection.
Hy- perspectral benchmark: Bridging the gap between hsi ap- plications through comprehensive dataset and pretraining
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.CV 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
SSFT is a lightweight spectral-spatial fusion transformer that ranks first on the HSI-Benchmark with less than 2% of the parameters of the previous best model.
citing papers explorer
-
IonMorphNet: Generalizable Learning of Ion Image Morphologies for Peak Picking in Mass Spectrometry Imaging
IonMorphNet is a ConvNeXt-based classifier trained on six spatial pattern classes from 53 MSI datasets that performs generalizable peak picking and improves mSCF1 by 7% over prior methods while also aiding tumor classification via ion selection.
-
SSFT: A Lightweight Spectral-Spatial Fusion Transformer for Generic Hyperspectral Classification
SSFT is a lightweight spectral-spatial fusion transformer that ranks first on the HSI-Benchmark with less than 2% of the parameters of the previous best model.