We present deepflash2, a deep learning solution that facilitates the objective and reliable segmentation of ambiguous bioimages through multi-expert annotations and integrated quality assurance. Thereby, deepflash2 addresses typical challenges that arise during training, evaluation, and application of deep learning models in bioimaging. The tool is embedded in an easy-to-use graphical user interface and offers best-in-class predictive performance for semantic and instance segmentation under economical usage of computational resources.
翻译:我们提出了深刻的思考2,这是一个深层次的学习解决方案,它通过多专家说明和综合质量保证,促进模糊的生物图像客观和可靠地分解。 因此,深层的思考2 解决了在生物成形过程中深层次学习模型的培训、评价和应用过程中出现的典型挑战。 该工具嵌入一个易于使用的图形用户界面,并在经济使用计算资源的情况下,为语义和实例分解提供最优级预测性表现。