Entomology Dataset - 70k insect images
|Total images||: 74,792|
|Resolution||: Up to 1024px|
|Storage size||: Up to 10 Gb|
|File format||: JPEG|
Discover the unparalleled diversity and beauty of the insect world through our meticulously curated collection: the Entomology Enriched Dataset. Comprising approximately 70,000 high-quality images, each complete with detailed, accurate tags, this resource is a treasure trove for anyone eager to delve into the microscopic world of insects.
Every image within our dataset is completely legally clean, obtained through a rigorous process that ensures respect for intellectual property rights.
The Entomology Enriched Dataset offers a wide range of applications across diverse fields:
1. AI Research and Development: Utilize the dataset to train and optimize machine learning models for insect image recognition, object detection, and classification tasks. Develop cutting-edge algorithms for automated insect identification and classification.
2. Agricultural Technology: In the realm of AgriTech, use machine learning models trained with our dataset to identify harmful pests and beneficial insects. This will enhance precision farming techniques, promote sustainable agriculture, and optimize integrated pest management strategies.
3. Bioinformatics and Computational Biology: Leverage the dataset to develop machine learning systems that can conduct large scale ecological surveys, automate species recognition tasks, and aid in biodiversity studies.
4. Public Health Informatics: Create machine learning models to identify and monitor disease-spreading insects. This can assist in the prediction, prevention, and control of insect-borne diseases, enhancing public health interventions.
Environment: Commercial stock
This dataset contains a tolerance margin of 10% to 15% of associated images which might not reflect 100% accuracy in the metadata or image. As example for the error margin: an empty Bee hive might appear due to its assocation to Bees. The maximum resolution of each image might vary. All metadata in this dataset had been created manually and might contain a low margin of error.
All descirptive metadata had been created manually. The metadata is based on descriptive image elements as well as conceptual and contextual keywords describing the situation.
The metadata is comprehensive following natural language keyword guides and is not standardized for a specific data paradigm.
We deliver the metadata in the following file formats:
- CSV spreadsheet
- JSON metadata file
- Txt2Img pairs