Data · dataset · 2023
A dataset of SEM images of atmospheric particles in Qingdao
Listed in ScienceDB
The study selected seven representative particle sampling points in Qingdao, intermittently collected atmospheric particle samples from 2016 to 2018, further obtained the SEM images of particles, and then observed their morphological characteristics.
Description
A total of 334 SEM images are selected from the particles with obvious characteristics. The obtained pictures are rotated by 90°, 180°, 270°, horizontal flip, brightness transformation, color balance and fuzzy processing to generate 7 groups of new experimental samples to be added to the dataset.
The dataset is expanded to obtain 2672 pictures. According to their morphological characteristics, they are divided into seven categories: chain smoke particles, flocculent smoke particles, fibrous particles, spherical particles, spherical like particles, irregular mineral particles and regular mineral particles. The SEM image dataset of atmospheric particles is established.
Read the rest (1 more)
The dataset established can be used to identify, classify and segment atmospheric particles by machine learning and other related methods.
Links
Where it is published
- DOI doi.org/10.11922/sciencedb.01170 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.11922%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Ocean & Atmospheric Science · Physics · Social Science
- Inferred from text
- Atmospheric sciences 72% · Image 75%
Provenance · 1 source records, 14 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.11922/sciencedb.01170 | 11 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].anzsrc:group:3701 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (72%) |
| 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:ocean-atmospheric | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:physics | 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 (75%) |
| 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 |