object detection in thermal images Computer Vision Project

overheadimagery

Updated 4 months ago

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Description

Overview

object detection in thermal images is a aggregation of multiple roboflow universe datasets to create a comprehensive dataset specifically tailored for transfer learning tasks in object detection using thermal imagery. This dataset has been curated to encompass a wide range of objects and scenarios commonly encountered in thermal imaging applications.

Classes

this dataset includes annotated images of car, people, cat, dog, using autodistill to fill in missing labels in between datasets.

Usage

  • To use the models trained on this data, ⭐ this dataset to access its model checkpoint and transfer learn this model on your own data.
    • Transfer learning from this dataset to other thermal tasks generally outperforms model training from COCO checkpoints.
  • To download this dataset for your own training, select versions on the right and select the most recent version.

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Cite This Project

LICENSE
CC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

                        @misc{
                            object-detection-in-thermal-images_dataset,
                            title = { object detection in thermal images Dataset },
                            type = { Open Source Dataset },
                            author = { overheadimagery },
                            howpublished = { \url{ https://universe.roboflow.com/overheadimagery-visqh/object-detection-in-thermal-images } },
                            url = { https://universe.roboflow.com/overheadimagery-visqh/object-detection-in-thermal-images },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2024 },
                            month = { may },
                            note = { visited on 2024-09-22 },
                            }
                        
                    

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