Few-shot learning for biotic stress classification of coffee leaves

In the last few years, deep neural networks have achieved promising results in several fields. However, one of the main limitations of these methods is the need for large-scale datasets to properly generalize. Few-shot learning methods emerged as an attempt to solve this shortcoming. Among the few-shot learning methods, there is a class of methods known as embedding learning or metric learning. These methods tackle the classification problem by learning to compare, needing fewer training data. One of the main problems in plant diseases and pests recognition is the lack of large public datasets available. Due to this difficulty, the field emerges as an intriguing application to evaluate the few-shot learning methods. The field is also relevant due to the social and economic importance of agriculture in several countries. In this work, datasets consisting of biotic stresses in coffee leaves are used as a case study to evaluate the performance of few-shot learning in classification and severity estimation tasks. We achieved competitive results compared with the ones reported in the literature in the classification task, with accuracy values close to 96%. Furthermore, we achieved superior results in the severity estimation task, obtaining 6.74% greater accuracy than the baseline

Extragalactic Magnetism with SOFIA (Legacy Program). I. The Magnetic Field in the Multiphase Interstellar Medium of M51

International audienceThe recent availability of high-resolution far-infrared (FIR) polarization observations of galaxies using HAWC+/SOFIA has facilitated studies of extragalactic magnetic fields in the cold and dense molecular disks. We investigate whether any significant structural differences are detectable in the kiloparsec-scale magnetic field of the grand design face-on spiral galaxy M51 when traced within the diffuse (radio) and the dense and cold (FIR) interstellar medium (ISM). Our analysis reveals a complex scenario where radio and FIR polarization observations do not necessarily trace the same magnetic field structure. We find that the magnetic field in the arms is wrapped tighter at 154 μm than at 3 and 6 cm; statistically significant lower values for the magnetic pitch angle are measured at FIR in the outskirts (R ≥ 7 kpc) of the galaxy. This difference is not detected in the interarm region. We find strong correlations of the polarization fraction and total intensity at FIR and radio with the gas column density and 12CO(1-0) velocity dispersion. We conclude that the arms show a relative increase of small-scale turbulent B-fields at regions with increasing column density and dispersion velocities of the molecular gas. No correlations are found with H I neutral gas. The star formation rate shows a clear correlation with the radio polarized intensity, which is not found in FIR, pointing to a small-scale dynamo-driven B-field amplification scenario. This work shows that multiwavelength polarization observations are key to disentangling the interlocked relation between star formation, magnetic fields, and gas kinematics in the multiphase ISM. * The SOFIA Legacy Group for Magnetic Fields in Galaxies software repository is available at https://github.com/galmagfields/hawc via the official project website, http://galmagfields.com/, and Zenodo/GitHub, https://doi.org/10.5281/zenodo.5116134