Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Xiongwei Huang"'
Publikováno v:
Avian Research, Vol 15, Iss , Pp 100162- (2024)
Biological specimens are fundamental for taxonomy and flora/fauna research. More importantly, they also play crucial roles in recording environmental impacts on morphology and behavior, which is vital for biodiversity research and conservation. Howev
Externí odkaz:
https://doaj.org/article/eb3be6d281014b8899696bf2af5419ac
Publikováno v:
Frontiers in Ecology and Evolution, Vol 11 (2023)
IntroductionSpecies inventories based on various data sources have been widely used in biodiversity research, conservation policy formulation, reserve designation and biodiversity resource management. In this paper, we explored the relationships of s
Externí odkaz:
https://doaj.org/article/f97b669d42fe471d96e7af1aa1d755d8
Publikováno v:
Avian Research, Vol 11, Iss 1, Pp 1-8 (2020)
Abstract Background Geographical distribution of endemic species and its multiple scale drivers are an important topic in biodiversity conservation, because these species are especially vulnerable to climate change and habitat degradation, and theref
Externí odkaz:
https://doaj.org/article/926e3020900f46ce9ac5800b70ec487e
Publikováno v:
Automation in Construction. 149:104792
Publikováno v:
Biodiversity and Conservation. 29:3287-3311
The taxonomic, spatial and temporal biases in digital accessible knowledge (DAK) are important considerations for macroecological research, effective biological conservation and the sustainable use of biological resources. Here, for the first time, w
Publikováno v:
Measurement Science and Technology. 34:024002
Computer-aided diagnosis of prostate ultrasound images is gradually being combined with deep learning to help detect and treat diseases. However, ultrasound images of the prostate have problems such as low resolution and unbalanced categories. In add
Additional file 3: Figure S1. Scatter plots of faunas (FAU) based endemic richness/ratio against georeferenced (GEO) endemic richness/ratio.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7ee42d2af906b95b3c4b73a010185906
Additional file 1: Table S1. List of the 56 endemic species included in our study.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::169c8ad9f7e497834a8332f0340985af
Additional file 2: Table S2. Correlations among explanatory variables.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5a37f3be7c8638284e1f0f1133e95511
Publikováno v:
Ecological Informatics. 61:101217
Species identification is a critical task of ecological research. Having accurate and intelligent methods of species identification would improve our ability to study and conserve biodiversity with saving much time and effort. But image-based deep le