Raw-Microscopy and Raw-Drone
Introduced by Oala et al. in Data Models for Dataset Drift Controls in Machine Learning With Optical Images
Raw-Microscopy:
940 raw bright-field microscopy images of human blood smear slides for leukocyte classification (microscopy/images/raw_scale100) with corresponding labels (microscopy/labels). 5,640 variations measured at six additional different intensities (microscopy/images/raw_scale001-raw_scale0075) 11,280 images of the raw sensor data processed through twelve different pipelines (microscopy/images/processed_views) Raw-Drone:
548 raw drone camera images for car segmentation (drone/images_tiles_256/raw_scale100) with corresponding binary segmentation mask (drone/masks_tiles_256). The images and the masks are cropped from 12 raw drone camera images (drone/images_full/raw_scale100) and 12 masks (drone/masks_full) of size 3648 by 5472. 3,288 variations measured at six additional different intensities (drone/images_tiles_256/raw_scale001-raw_scale075). 6,576 images of the raw sensor data processed through twelve different pipelines (drone/images_tiles_256/processed_views). Detailed datasheets for the two datasets can be found in the appendices of https://arxiv.org/abs/2211.02578.
Papers
| Paper | Code | Results | Date | Stars |
|---|
