PeakTransformer utilizes a 1D-CNN + Transformer hybrid architecture to mathematically deconvolve highly overlapping DPV signals, predicting Dopamine and Hydroquinone concentrations instantly.
Hardware limits in sensor technology result in overlapping oxidation potentials. Distinguishing DA (+0.05V) and HQ (-0.03V) traditionally requires complex chemical modification.
By leveraging self-attention mechanisms via a custom Transformer architecture, our model effectively "learns" the shapes and areas of the analytes even under severe noise.
A fully integrated end-to-end SAAS interface. Upload your raw hardware data, test against synthetic benchmarks, and get instant concentration predictions in µM without coding.