Omkar2118/datasets huggingface dataset:
YIM Dataset
Full name: Yeast Cells in Microstructures Dataset

An instance segmentation dataset of yeast cells in microstructures. The dataset includes 493 densely annotated microscopy images. For more information see the paper "An Instance Segmentation Dataset of Yeast Cells in Microstructures".

Introducing paper: An Instance Segmentation Dataset of Yeast Cells in Microstructures
Trajectory calibration experiments

Data and experiments for motion-based extrinsic calibration using [trajectory_calibration]. The data was generated for evaluating hand-eye calibration algorithms in extrinsic sensor-to-sensor calibration.

The repository is organised as follows:

```
├── calib
│   └── *.csv  # The output calibration values
├── kitti_tests
│   └── ...    # The trajectories generated from KITTI data
├── matlab
│   └── ...    # Matlab files to generate simulation data
├── simulation_tests
│   └── ...    # The generated simulation data
├── *.py       # Scripts to run the calibration experiments
└── README.md
```

If you use the data in an academic context, please cite:

    @article{valimaki2023,
      author = {Välimäki, Tuomas and Garigipati, Bharath and Ghabcheloo, Reza},
      title = {Motion-Based Extrinsic Sensor-to-Sensor Calibration: Effect of Reference Frame Selection for New and Existing Methods},
      journal = {Sensors},
      volume = {23},
      year = {2023},
      number = {7},
      pages = {3740},
      url = {https://www.mdpi.com/1424-8220/23/7/3740},
      issn = {1424-8220},
      doi = {10.3390/s23073740}
    }

[trajectory_calibration]: https://github.com/tau-alma/trajectory_calibration

Introducing paper: Motion-based extrinsic sensor-to-sensor calibration: Effect of reference frame selection for new and existing methods