  We construct a procedure to separate boosted Higgs bosons decaying into
hadrons, from the background due to strong interactions. We employ the Lund jet
plane to obtain a theoretically well-motivated representation of the jets of
interest and we use the resulting images as the input to a convolutional neural
network classifier. In particular, we consider two different decay modes of the
Higgs boson, namely into a pair of bottom quarks or into light jets, against
the respective backgrounds. For each case, we consider both a moderate- and
high- boost scenario. The performance of the tagger is compared to what is
achieved using a traditional single-variable analysis which exploits a QCD
inspired color-singlet tagger, namely the jet color ring observable.
