Translating satellite imagery into maps requires intensive effort and time, especially leading to inaccurate maps of the affected regions during disaster and conflict. The combination of availability of recent datasets and advances in computer vision made through deep learning paved the way toward automated satellite image translation. To facilitate research in this direction, we introduce the Satellite Imagery Competition using a modified SpaceNet dataset. Participants had to come up with different segmentation models to detect positions of buildings on satellite images. In this work, we present five approaches based on improvements of U-Net and Mask R-Convolutional Neuronal Networks models, coupled with unique training adaptations using boosting algorithms, morphological filter, Conditional Random Fields and custom losses. The good results—as high as AP=0.937 and AR=0.959—from these models demonstrate the feasibility of Deep Learning in automated satellite image annotation.
The clinical methods of diagnosis are described and it is emphasized that their useful application increases with practice. Details are given of relevant cases seen during a period of 6 months. There were two cases of bronchitis, two cases of pulmonary congestion, secondary to cardiac insufficiency, one of inflammation due to migrating roundworm larvae and two cases of tumour metastasis.
Résumé. On décrit les méthodes cliniques de diagnostic et on souligne le fait que l'utilité de leur emploi augmente avec l'augmentation de la pratique. On donne des détails des cas caractéristiques observés au cours d'une période de 6 mois; il s'agissait de deux cas de bronchite, de deux cas de congestion pulmonaire secondaire à une insuffisance cardiaque, d'un cas d'inflammation due à la migration de larves d'Ascaris et de deux métatases de tumeurs.
Zusammenfassung. Die klinischen Methoden der Diagnose werden beschrieben, und es wird betont, dass mit zunehmender Praxis sich ihre erfolgreiche Anwendung verbessert. Einzelheiten über aufschlussreiche Fälle in einem Zeitraum von 6 Monaten werden angegeben. Es handelte sich um zwei Fälle von Bronchitis, zwei Fälle von Lungenstauung nach Herzinsuffizienz, einen von Entzündung infolge wandernder Fadenwurmlarven und zwei Fälle von metastatischem Tumor.
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