相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。Deep learning versus Object-based Image Analysis (OBIA) in weed mapping of UAV imagery
Huasheng Huang et al.
INTERNATIONAL JOURNAL OF REMOTE SENSING (2020)
Identifying Species and Monitoring Understorey from UAS-Derived Data: A Literature Review and Future Directions
Lorna Hernandez-Santin et al.
DRONES (2019)
Efficient and robust deep networks for semantic segmentation
Gabriel L. Oliveira et al.
INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH (2018)
Image-based recognition framework for robotic weed control systems
Tsampikos Kounalakis et al.
MULTIMEDIA TOOLS AND APPLICATIONS (2018)
Fusion of pixel and object-based features for weed mapping using unmanned aerial vehicle imagery
Junfeng Gao et al.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION (2018)
The potential of Unmanned Aerial Systems: A tool towards precision classification of hard-to-distinguish vegetation types?
Jan Komarek et al.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION (2018)
A fully convolutional network for weed mapping of unmanned aerial vehicle (UAV) imagery
Huasheng Huang et al.
PLOS ONE (2018)
On the Use of Unmanned Aerial Systems for Environmental Monitoring
Salvatore Manfreda et al.
REMOTE SENSING (2018)
Emergence and root fragments regeneration of Rumex species
Khalid S. Alshallash
ANNALS OF AGRICULTURAL SCIENCE (2018)
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
Vijay Badrinarayanan et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2017)
Fully Convolutional Networks for Semantic Segmentation
Evan Shelhamer et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2017)
Timing Is Important: Unmanned Aircraft vs. Satellite Imagery in Plant Invasion Monitoring
Jana Mullerova et al.
FRONTIERS IN PLANT SCIENCE (2017)
Identifying species from the air: UAVs and the very high resolution challenge for plant conservation
Susana Baena et al.
PLOS ONE (2017)
Controlled comparison of machine vision algorithms for Rumex and Urtica detection in grassland
A. Binch et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2017)
Object-based early monitoring of a grass weed in a grass crop using high resolution UAV imagery
Francisca Lopez-Granados et al.
AGRONOMY FOR SUSTAINABLE DEVELOPMENT (2016)
A survey of image processing techniques for plant extraction and segmentation in the field
Esmael Hamuda et al.
COMPUTERS AND ELECTRONICS IN AGRICULTURE (2016)
Mapping of riparian invasive species with supervised classification of Unmanned Aerial System (UAS) imagery
Adrien Michez et al.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION (2016)
A comparison of pixel-based and object-based approaches for land use land cover classification in semi-arid areas, Sudan
H. E. Adam et al.
8TH IGRSM INTERNATIONAL CONFERENCE AND EXHIBITION ON GEOSPATIAL & REMOTE SENSING (IGRSM 2016) (2016)
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky et al.
INTERNATIONAL JOURNAL OF COMPUTER VISION (2015)
Feature Learning Based Approach for Weed Classification Using High Resolution Aerial Images from a Digital Camera Mounted on a UAV
Calvin Hung et al.
REMOTE SENSING (2014)
Accurate Multiple View 3D Reconstruction Using Patch-Based Stereo for Large-Scale Scenes
Shuhan Shen
IEEE TRANSACTIONS ON IMAGE PROCESSING (2013)
Weed Mapping in Early-Season Maize Fields Using Object-Based Analysis of Unmanned Aerial Vehicle (UAV) Images
Jose Manuel Pena et al.
PLOS ONE (2013)
Classification of crops and weeds from digital images: A support vector machine approach
Faisal Ahmed et al.
CROP PROTECTION (2012)
A Robot to Detect and Control Broad-Leaved Dock (Rumex obtusifolius L.) in Grassland
Frits K. van Evert et al.
JOURNAL OF FIELD ROBOTICS (2011)
Robust Crop and Weed Segmentation under Uncontrolled Outdoor Illumination
Hong Y. Jeon et al.
SENSORS (2011)
A systematic analysis of performance measures for classification tasks
Marina Sokolova et al.
INFORMATION PROCESSING & MANAGEMENT (2009)
Identification of broad-leaved dock (Rumex obtusifolius L.) on grassland by means of digital image processing
Steffen Gebhardt et al.
PRECISION AGRICULTURE (2006)
Nutritive value of broad-leaved dock (Rumex obtusifolius L.) and its effect on the quality of grass silages
S Hejduk et al.
CZECH JOURNAL OF ANIMAL SCIENCE (2004)
Ecology and non-chemical control of Rumex crispus and R-obtusifolius (Polygonaceae):: a review
JG Zaller
WEED RESEARCH (2004)
Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information
UC Benz et al.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2004)