An image dataset of fruitfly species (Bactrocera Zonata and Bactrocera Dorsalis) and automated species classification through object detection
This data article describes the image dataset collection and annotation of the two most common fruitfly species Bactrocera Zonata and Bactrocera Dorsalis. The dataset is released as a collection of more than 2000 images captured through two sources: images of specially reared fruitfly species in lab...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-08-01
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| Series: | Data in Brief |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340922005625 |
| _version_ | 1828154594612477952 |
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| author | Sana Tariq Ayesha Hakim Awais Ahmad Siddiqi Muhammad Owais |
| author_facet | Sana Tariq Ayesha Hakim Awais Ahmad Siddiqi Muhammad Owais |
| author_sort | Sana Tariq |
| collection | DOAJ |
| description | This data article describes the image dataset collection and annotation of the two most common fruitfly species Bactrocera Zonata and Bactrocera Dorsalis. The dataset is released as a collection of more than 2000 images captured through two sources: images of specially reared fruitfly species in laboratory captured by (48-megapixels) smartphone camera, and images of fruitflies captured by (8-megapixels) Raspberry Pi camera through insect traps installed in fruit orchards. Each image sample is associated with a ground truth label that mentions the fruit fly species. The dataset has been classified and annotated using the object detection method into two fruitfly species with an average 85% accuracy. The results of classification and annotation have been validated by expert entomologists by manually examining test samples in a laboratory setting. This dataset is best suited for developing smart monitoring systems to provide advisory services to farmers through mobile applications that provides real-time information about fruitfly species for effective control and management. |
| first_indexed | 2024-04-11T22:43:15Z |
| format | Article |
| id | doaj.art-2f664af78b5548bdbc5da41392916839 |
| institution | Directory Open Access Journal |
| issn | 2352-3409 |
| language | English |
| last_indexed | 2024-04-11T22:43:15Z |
| publishDate | 2022-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Data in Brief |
| spelling | doaj.art-2f664af78b5548bdbc5da413929168392022-12-22T03:58:55ZengElsevierData in Brief2352-34092022-08-0143108366An image dataset of fruitfly species (Bactrocera Zonata and Bactrocera Dorsalis) and automated species classification through object detectionSana Tariq0Ayesha Hakim1Awais Ahmad Siddiqi2Muhammad Owais3Department of Computer Science, Muhammad Nawaz Shareef University of Agriculture (MNSUA), Multan, PakistanDepartment of Computer Science, Muhammad Nawaz Shareef University of Agriculture (MNSUA), Multan, Pakistan; Corresponding author.School of Software, Tsinghua University, P.R. ChinaDepartment of Computer Science, Muhammad Nawaz Shareef University of Agriculture (MNSUA), Multan, PakistanThis data article describes the image dataset collection and annotation of the two most common fruitfly species Bactrocera Zonata and Bactrocera Dorsalis. The dataset is released as a collection of more than 2000 images captured through two sources: images of specially reared fruitfly species in laboratory captured by (48-megapixels) smartphone camera, and images of fruitflies captured by (8-megapixels) Raspberry Pi camera through insect traps installed in fruit orchards. Each image sample is associated with a ground truth label that mentions the fruit fly species. The dataset has been classified and annotated using the object detection method into two fruitfly species with an average 85% accuracy. The results of classification and annotation have been validated by expert entomologists by manually examining test samples in a laboratory setting. This dataset is best suited for developing smart monitoring systems to provide advisory services to farmers through mobile applications that provides real-time information about fruitfly species for effective control and management.http://www.sciencedirect.com/science/article/pii/S2352340922005625FruitflyBactrocera ZonataBactrocera DorsalisMicrocontrollerSmart trapIoT |
| spellingShingle | Sana Tariq Ayesha Hakim Awais Ahmad Siddiqi Muhammad Owais An image dataset of fruitfly species (Bactrocera Zonata and Bactrocera Dorsalis) and automated species classification through object detection Data in Brief Fruitfly Bactrocera Zonata Bactrocera Dorsalis Microcontroller Smart trap IoT |
| title | An image dataset of fruitfly species (Bactrocera Zonata and Bactrocera Dorsalis) and automated species classification through object detection |
| title_full | An image dataset of fruitfly species (Bactrocera Zonata and Bactrocera Dorsalis) and automated species classification through object detection |
| title_fullStr | An image dataset of fruitfly species (Bactrocera Zonata and Bactrocera Dorsalis) and automated species classification through object detection |
| title_full_unstemmed | An image dataset of fruitfly species (Bactrocera Zonata and Bactrocera Dorsalis) and automated species classification through object detection |
| title_short | An image dataset of fruitfly species (Bactrocera Zonata and Bactrocera Dorsalis) and automated species classification through object detection |
| title_sort | image dataset of fruitfly species bactrocera zonata and bactrocera dorsalis and automated species classification through object detection |
| topic | Fruitfly Bactrocera Zonata Bactrocera Dorsalis Microcontroller Smart trap IoT |
| url | http://www.sciencedirect.com/science/article/pii/S2352340922005625 |
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