RoblabWhGe
基于SenseTime可变形DETR架构微调的火灾检测模型，支持火焰、车辆和人体多目标检测
SenseTime
可变形DETR是一种基于Transformer的目标检测模型，通过边界框优化和两阶段检测实现端到端训练，适用于COCO数据集。
可变形DETR是一种端到端的目标检测模型，结合了Transformer架构和可变形卷积的优势，在COCO数据集上实现了高效的目标检测。
可变形检测变换器（Deformable DETR）单尺度模型，专为目标检测任务设计，采用端到端训练方式，在COCO 2017数据集上表现优异。
可变形DETR是一种端到端的目标检测模型，结合了Transformer架构和可变形卷积的优势，在COCO数据集上训练而成。
可变形DETR是一种端到端目标检测模型，使用Transformer架构和可变形注意力机制改进检测性能。
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