Clear2Fog generates realistic synthetic fog from clear scenes, enabling mixed-density training that outperforms full fixed-density data and improves real-world performance by 1.67 mAP after learning-rate adjustment.
Faster R-CNN: Towards real- time object detection with region proposal networks
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SegResNet trained with assorted precision achieves Dice scores of 0.84 overall, 0.84 for tumor core, 0.90 for whole tumor, and 0.79 for enhancing tumor.
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A Data Efficiency Study of Synthetic Fog for Object Detection Using the Clear2Fog Pipeline
Clear2Fog generates realistic synthetic fog from clear scenes, enabling mixed-density training that outperforms full fixed-density data and improves real-world performance by 1.67 mAP after learning-rate adjustment.
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Enhanced 3D Brain Tumor Segmentation Using Assorted Precision Training
SegResNet trained with assorted precision achieves Dice scores of 0.84 overall, 0.84 for tumor core, 0.90 for whole tumor, and 0.79 for enhancing tumor.