dataService

您的位置: 首页 > 数据服务 > 数据列表页

筛选

共检索到12条 ,权限内显示50条;

Data from: Using deep learning to quantify the beauty of outdoor places
负责人:
关键词:
Deep learning;online data;Environmental aesthetics;wellbeing;convolutional neural networks
DOI:
doi:10.5061/dryad.rq4s3
摘要:
ces Convolutional Neural Network, might help us understand what beautiful outdoor spaces are composed of. We discover that, as well as natural features such as ‘Coast’, ‘Mountain
Data from: A convolutional neural network for detecting sea turtles in drone imagery
负责人:
Gray, Patrick C.
关键词:
convolutional neural networks deep learning for ecology marine megafauna marine population monitoring object detection sea turtles unoccupied aircraft systems
DOI:
doi:10.5061/dryad.5h06vv2
摘要:
ted in the images or video acquired during each flight. Neural networks are emerging as a powerful tool for automating object detection across data domains
Data from: Accurate inference of tree topologies from multiple sequence alignments using deep learning
负责人:
关键词:
Supervised Machine Learning;convolutional neuronal network;phylogenetics
DOI:
doi:10.5061/dryad.ct2895s
摘要:
techniques have made inroads on a number of both new and longstanding problems in biological research. Here we designed a deep convolutional neural network
Data from: High-throughput adaptive sampling for whole-slide histopathology image analysis (HASHI) via convolutional neural networks: applicati
负责人:
关键词:
learning;image analysis;Invasive tumors;Histopathology;Neurons;Neural networks;Imaging techniques
DOI:
doi:10.5061/dryad.1g2nt41
摘要:
ding. Convolutional neural network (CNN) is the most popular representation learning method for computer vision tasks, which have been successfully applied in digital
Data from: Improving automated annotation of benthic survey images using wide-band fluorescence
负责人:
关键词:
coral reefs;computer vision;Platygyra;Acropora;Pocillopora;fluorescence;Multi-modal imaging;Stylophora;Faviidae;Deep learning;2015;Millepora;Machine Learning;ecological surveys
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: CORIGAN: Assessing multiple species and interactions within images
负责人:
关键词:
Convolutional Neural Network;Animal detection;image processing;trophic networks;Metamasius spp.;Pheidole radoszkowskii;Interaction study;Cosmopolites sordidus;Camponotus atriceps;Sentinel prey study;On-field image;Solenopsis geminata
DOI:
doi:10.5061/dryad.t03b7b8
摘要:
and non?trophic interactions network describing the studied community. 4.CORIGAN relies on generic properties of the detected animals and can be used for a wide range of studies
Data from: Deep learning for bridge load capacity estimation in post-disaster and -conflict zones
负责人:
关键词:
Bridges;Load Rating;Design Load;convolutional neural networks;Deep learning
DOI:
doi:10.5061/dryad.6br51tn
摘要:
mate the load carrying capacity from crowd sourced images. A new convolutional neural network architecture is trained on data from over 6000 bridges, which will bene
Monitoring crop health, growth and its stand count attributes using UAV based precision agriculture: a study in tropical farmland of Thailand
负责人:
Teerayut Horanont, Advisor
关键词:
NDVI Modified infrared CMOS sensor UAV photogrammetry Multi-temporal CSM Crop growth Deep-learning Object detection Crop Counting
DOI:
doi:10.14457/tu.the.2017.344
摘要:
in an aerial imagery. The convolutional neural network implemented in this study was based open source tensorflow implementation of the darknet framework named, Darkflow
Data from: Unsupervised machine learning reveals mimicry complexes in bumble bees occur along a perceptual continuum
负责人:
关键词:
Biogeography;Convolutional Neural Network;coloration;Machine Learning;Müllerian mimicry;Bombus
DOI:
doi:10.5061/dryad.sd7cd06
摘要:
on spatially, rather than exhibit discrete boundaries. Additionally, examination of colour pattern transition zones of three comimicking, polymorphic species

首页上一页12下一页尾页

意 见 箱

匿名:登录

个人用户登录

找回密码

第三方账号登录

忘记密码

个人用户注册

必须为有效邮箱
6~16位数字与字母组合
6~16位数字与字母组合
请输入正确的手机号码

信息补充