Data · dataset · 2023
GalliformeSpectra: A Hen Breed Dataset
Listed in ScienceDB
This dataset includes a variety of low-resolution images showcasing ten globally recognized hen breeds.
Description
These breeds were carefully chosen from different parts of the world to ensure a diverse and comprehensive representation. The dataset serves as a visual resource, offering a detailed depiction of the unique characteristics of these hen breeds, which aids in their accurate classification.
It consists of ten distinct categories: Bielefeld, Blackorpington, Brahma, Buckeye, Fayoumi, Leghorn, Newhampshire, Plymouthrock, Sussex, and Turken, comprising a total of 1010 original JPG images that were later resized and converted to PNG format. After applying augmentation techniques, the total number of images increased to 5050. The dataset is organized into three variations: one with original images, another with resized images, and a third with augmented images.
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Each variation is further divided into ten separate folders, each dedicated to a specific hen breed. The images vary in size and have been subjected to data augmentation, which is essential for training machine vision deep learning models. Augmentation includes transformations like left and right flips, random adjustments in brightness (0.7-1.1), and random zoom (90% area).
Consequently, an additional 505 augmented images were created from the original images in each category, resulting in a dataset comprising a total of 5050 augmented images (505 per category).
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.12798 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Computer Science & AI · Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Image 65% · Machine learning 70%
Provenance · 1 source records, 13 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.12798 | 9 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].anzsrc:group:4611 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (70%) |
| concepts[field].local:field:computer-science-ai | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[modality].local:modality:image | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (65%) |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/rights |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |