筛选
科学数据
统计数据
共检索到167条 ,权限内显示50条;
Data from: Measuring agreement among experts in classifying camera images of similar species
- 负责人：
- Gooliaff, TJ
- DOI：
- doi:10.5061/dryad.1g71qj2
- 摘要：
- ny wildlife images for which correct species classification is crucial; even low misclassification rates can result in erroneous estimati
Data from: Phenotype classification of zebrafish embryos by supervised learning
- 负责人：
- DOI：
- doi:10.5061/dryad.23d30
- 摘要：
- zebrafish embryos according to their defects by using an image analysis approach based on supervised machine learning. We show that, compared to manual classification
Data from: Improving automated annotation of benthic survey images using wide-band fluorescence
- 负责人：
- DOI：
- doi:10.5061/dryad.t4362
- 摘要：
- d on convolutional neural networks was developed. Our results demonstrate a 22% reduction of classification error-rate when using both images types compared to only using reflectance
Data from: Predicting classifier performance with limited training data: applications to computer-aided diagnosis in breast and prostate cancer
- 负责人：
- DOI：
- doi:10.5061/dryad.m5n98
- 摘要：
- Clinical trials increasingly employ medical imaging data in conjunction with supervised classifiers, where the latter require large amounts
Data from: Automated taxonomic identification of insects with expert-level accuracy using effective feature transfer from convolutional networks
- 负责人：
- 关键词：
- DOI：
- doi:10.5061/dryad.20ch6p5
- 摘要：
- ble for taxonomic tasks. This can be addressed using feature transfer: a CNN that has been pretrained on a generic image classification task is exposed
Data from: Machine learning to classify animal species in camera trap images: applications in ecology
- 负责人：
- 关键词：
- DOI：
- doi:10.5061/dryad.st8f5n7
- 摘要：
- containing an animal in the dataset from Tanzania. We provide an r package (Machine Learning for Wildlife Image Classification) that allows the us
Data from: Assessing the sensitivity of biodiversity indices used to inform fire management
- 负责人：
- DOI：
- doi:10.5061/dryad.2317g
- 摘要：
- management targets. However, the sensitivity of biodiversity indices to the data, landscape classification and conservation values underpinning them are rarely
Data from: Determining the subcellular location of new proteins from microscope images using local features
- 负责人：
- DOI：
- doi:10.5061/dryad.2vm70
- 摘要：
- features help achieve classification improvements for other previously studied datasets.
Data from: Modeling avian biodiversity using raw, unclassified satellite imagery
- 负责人：
- DOI：
- doi:10.5061/dryad.sk792
- 摘要：
- Applications of remote sensing for biodiversity conservation typically rely on image classifications that do not capture variability within coarse
Data from: Comparing radiomic classifiers and classifier ensembles for detection of peripheral zone prostate tumors on T2-weighted MRI: a multi-si
- 负责人：
- DOI：
- doi:10.5061/dryad.026cj63
- 摘要：
- Background: For most computer-aided diagnosis (CAD) problems involving prostate cancer detection via medical imaging data, the choice of classifier
