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A. Moghimi, M. Welzel, T. Celik, and T. Schlurmann, "A Comparative Performance Analysis of Popular Deep Learning Models and Segment Anything Model (SAM) for River Water Segmentation in Close-Range Remote Sensing Imagery,"
ClusterClient es una herramienta interactiva diseñada para segmentar clientes automáticamente a partir de datos como ingresos anuales y puntuación de gasto.
Streamline fluorescent microscopy workflows with these scripts. This collection provides automated cell segmentation & tracking using TrackMate, featuring two-step segmentation, flexible temporal/spatial tracking, and efficient analysis of large datasets. Ideal for researchers automating imaging analysis.