Computer Vision, IoT and Data Fusion for Crop Disease Detection Using Machine Learning: A Survey and Ongoing Research
出版年份 2021 全文链接
标题
Computer Vision, IoT and Data Fusion for Crop Disease Detection Using Machine Learning: A Survey and Ongoing Research
作者
关键词
-
出版物
Remote Sensing
Volume 13, Issue 13, Pages 2486
出版商
MDPI AG
发表日期
2021-06-25
DOI
10.3390/rs13132486
参考文献
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。- Towards a Multi-Temporal Deep Learning Approach for Mapping Urban Fabric Using Sentinel 2 Images
- (2020) Lamiae El Mendili et al. Remote Sensing
- An effective automatic system deployed in agricultural Internet of Things using Multi-Context Fusion Network towards crop disease recognition in the wild
- (2020) Yushan Zhao et al. APPLIED SOFT COMPUTING
- Multilevel data fusion for the internet of things in smart agriculture
- (2020) Andrei B.B. Torres et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Comparison of machine learning methods for citrus greening detection on UAV multispectral images
- (2020) Yubin Lan et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Detection of Xylella fastidiosa infection symptoms with airborne multispectral and thermal imagery: Assessing bandset reduction performance from hyperspectral analysis
- (2020) T. Poblete et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- Applications of UAV Thermal Imagery in Precision Agriculture: State of the Art and Future Research Outlook
- (2020) Gaetano Messina et al. Remote Sensing
- Crop Monitoring Using Satellite/UAV Data Fusion and Machine Learning
- (2020) Maitiniyazi Maimaitijiang et al. Remote Sensing
- Remote Sensing and Precision Agriculture Technologies for Crop Disease Detection and Management with a Practical Application Example
- (2020) Chenghai Yang Engineering
- Recognition of diseased Pinus trees in UAV images using deep learning and AdaBoost classifier
- (2020) Gensheng Hu et al. BIOSYSTEMS ENGINEERING
- High-resolution satellite imagery applications in crop phenotyping: An overview
- (2020) Chongyuan Zhang et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- An end-to-end model for rice yield prediction using deep learning fusion
- (2020) Zheng Chu et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Hyperspectral imaging and 3D technologies for plant phenotyping: From satellite to close-range sensing
- (2020) Huajian Liu et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Vine disease detection in UAV multispectral images using optimized image registration and deep learning segmentation approach
- (2020) Mohamed Kerkech et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Deep learning on edge: Extracting field boundaries from satellite images with a convolutional neural network
- (2020) François Waldner et al. REMOTE SENSING OF ENVIRONMENT
- On Robustness of Multi-Modal Fusion—Robotics Perspective
- (2020) Michal Bednarek et al. Electronics
- In-field proximal sensing of septoria tritici blotch, stripe rust and brown rust in winter wheat by means of reflectance and textural features from multispectral imagery
- (2020) Romain Bebronne et al. BIOSYSTEMS ENGINEERING
- Detecting powdery mildew disease in squash at different stages using UAV-based hyperspectral imaging and artificial intelligence
- (2020) Jaafar Abdulridha et al. BIOSYSTEMS ENGINEERING
- Occurrence prediction of cotton pests and diseases by bidirectional long short-term memory networks with climate and atmosphere circulation
- (2020) Peng Chen et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Comparison of convolution neural networks for smartphone image based real time classification of citrus leaf disease
- (2020) Utpal Barman et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Crop yield prediction using machine learning: A systematic literature review
- (2020) Thomas van Klompenburg et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- MobileNet Based Apple Leaf Diseases Identification
- (2020) Chongke Bi et al. MOBILE NETWORKS & APPLICATIONS
- Combination of multiple classifiers for automatic recognition of diseases and damages on plant leaves
- (2020) Ismail El Massi et al. Signal Image and Video Processing
- VddNet: Vine Disease Detection Network Based on Multispectral Images and Depth Map
- (2020) Mohamed Kerkech et al. Remote Sensing
- Applications of Remote Sensing in Precision Agriculture: A Review
- (2020) Rajendra P. Sishodia et al. Remote Sensing
- Review of the State of the Art of Deep Learning for Plant Diseases: A Broad Analysis and Discussion
- (2020) Reem Ibrahim Hasan et al. Plants-Basel
- Identifying sunflower lodging based on image fusion and deep semantic segmentation with UAV remote sensing imaging
- (2020) Zhishuang Song et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Remote Sensing in Agriculture—Accomplishments, Limitations, and Opportunities
- (2020) Sami Khanal et al. Remote Sensing
- Plant leaf disease classification using EfficientNet deep learning model
- (2020) Ümit Atila et al. Ecological Informatics
- Evaluating annual spruce budworm defoliation using change detection of vegetation indices calculated from satellite hyperspectral imagery
- (2020) Shawn D. Donovan et al. REMOTE SENSING OF ENVIRONMENT
- Building Extraction in Multitemporal High-Resolution Remote Sensing Imagery Using a Multifeature LSTM Network
- (2020) Yuhan Wang et al. IEEE Geoscience and Remote Sensing Letters
- Multisource and Multitemporal Data Fusion in Remote Sensing: A Comprehensive Review of the State of the Art
- (2019) Pedram Ghamisi et al. IEEE Geoscience and Remote Sensing Magazine
- Development of an open sensorized platform in a smart agriculture context: A vineyard support system for monitoring mildew disease
- (2019) Sergio Trilles et al. Sustainable Computing-Informatics & Systems
- Temporal Convolutional Neural Network for the Classification of Satellite Image Time Series
- (2019) Charlotte Pelletier et al. Remote Sensing
- State-of-the-Art Internet of Things in Protected Agriculture
- (2019) Xiaojie Shi et al. SENSORS
- Integrating Growth and Environmental Parameters to Discriminate Powdery Mildew and Aphid of Winter Wheat Using Bi-Temporal Landsat-8 Imagery
- (2019) Huiqin Ma et al. Remote Sensing
- Detection of nutrition deficiencies in plants using proximal images and machine learning: A review
- (2019) Jayme Garcia Arnal Barbedo COMPUTERS AND ELECTRONICS IN AGRICULTURE
- UAV-Based Remote Sensing Technique to Detect Citrus Canker Disease Utilizing Hyperspectral Imaging and Machine Learning
- (2019) Jaafar Abdulridha et al. Remote Sensing
- Wireless sensor networks for greenhouses: An end-to-end review
- (2019) Aarti Kochhar et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Monitoring plant diseases and pests through remote sensing technology: A review
- (2019) Jingcheng Zhang et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- An IoT-based cognitive monitoring system for early plant disease forecast
- (2019) Ahmed Khattab et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Crop conditional Convolutional Neural Networks for massive multi-crop plant disease classification over cell phone acquired images taken on real field conditions
- (2019) Artzai Picon et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Detection of coffee berry necrosis by digital image processing of landsat 8 oli satellite imagery
- (2019) Jonathan da Rocha Miranda et al. International Journal of Applied Earth Observation and Geoinformation
- A survey of unmanned aerial sensing solutions in precision agriculture
- (2019) Anandarup Mukherjee et al. JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
- Soybean yield prediction from UAV using multimodal data fusion and deep learning
- (2019) Maitiniyazi Maimaitijiang et al. REMOTE SENSING OF ENVIRONMENT
- Deep learning-based fusion of Landsat-8 and Sentinel-2 images for a harmonized surface reflectance product
- (2019) Zhenfeng Shao et al. REMOTE SENSING OF ENVIRONMENT
- A survey on machine learning for data fusion
- (2019) Tong Meng et al. Information Fusion
- Deep learning in agriculture: A survey
- (2018) Andreas Kamilaris et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Multimodal Machine Learning: A Survey and Taxonomy
- (2018) Tadas Baltrusaitis et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Heavy metal-induced stress in rice crops detected using multi-temporal Sentinel-2 satellite images
- (2018) Meiling Liu et al. SCIENCE OF THE TOTAL ENVIRONMENT
- New Spectral Index for Detecting Wheat Yellow Rust Using Sentinel-2 Multispectral Imagery
- (2018) Qiong Zheng et al. SENSORS
- Classifying Wheat Hyperspectral Pixels of Healthy Heads and Fusarium Head Blight Disease Using a Deep Neural Network in the Wild Field
- (2018) Xiu Jin et al. Remote Sensing
- 3D Convolutional Neural Networks for Crop Classification with Multi-Temporal Remote Sensing Images
- (2018) Shunping Ji et al. Remote Sensing
- Spatiotemporal Fusion of Multisource Remote Sensing Data: Literature Survey, Taxonomy, Principles, Applications, and Future Directions
- (2018) et al. Remote Sensing
- Evaluating Late Blight Severity in Potato Crops Using Unmanned Aerial Vehicles and Machine Learning Algorithms
- (2018) Julio Duarte-Carvajalino et al. Remote Sensing
- The State-of-the-Art of Knowledge-Intensive Agriculture: A Review on Applied Sensing Systems and Data Analytics
- (2018) Barun Basnet et al. Journal of Sensors
- Deep leaning approach with colorimetric spaces and vegetation indices for vine diseases detection in UAV images
- (2018) Mohamed Kerkech et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Wheat yellow rust monitoring by learning from multispectral UAV aerial imagery
- (2018) Jinya Su et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- A Survey on Data Fusion in Internet of Things: Towards Secure and Privacy-Preserving Fusion
- (2018) Wenxiu Ding et al. Information Fusion
- Identification of Soybean Foliar Diseases Using Unmanned Aerial Vehicle Images
- (2017) Everton Castelao Tetila et al. IEEE Geoscience and Remote Sensing Letters
- Deep Multimodal Learning: A Survey on Recent Advances and Trends
- (2017) Dhanesh Ramachandram et al. IEEE SIGNAL PROCESSING MAGAZINE
- Convolutional Neural Networks for Large-Scale Remote-Sensing Image Classification
- (2017) Emmanuel Maggiori et al. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
- Unmanned Aerial System (UAS)-based phenotyping of soybean using multi-sensor data fusion and extreme learning machine
- (2017) Maitiniyazi Maimaitijiang et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- Habitat monitoring to evaluate crop disease and pest distributions based on multi-source satellite remote sensing imagery
- (2017) Lin Yuan et al. OPTIK
- Hyperspectral image analysis techniques for the detection and classification of the early onset of plant disease and stress
- (2017) Amy Lowe et al. Plant Methods
- Sensors key to advances in precision agriculture
- (2017) Robert Bogue Sensor Review
- An Adaptive Multi-Sensor Data Fusion Method Based on Deep Convolutional Neural Networks for Fault Diagnosis of Planetary Gearbox
- (2017) Luyang Jing et al. SENSORS
- Hyperspectral Imaging for Presymptomatic Detection of Tobacco Disease with Successive Projections Algorithm and Machine-learning Classifiers
- (2017) Hongyan Zhu et al. Scientific Reports
- Hyperspectral Imaging: A Review on UAV-Based Sensors, Data Processing and Applications for Agriculture and Forestry
- (2017) Telmo Adão et al. Remote Sensing
- Detection of Flavescence dorée Grapevine Disease Using Unmanned Aerial Vehicle (UAV) Multispectral Imagery
- (2017) Johanna Albetis et al. Remote Sensing
- Soybean Disease Monitoring with Leaf Reflectance
- (2017) Sreekala Bajwa et al. Remote Sensing
- Remote hyperspectral imaging of grapevine leafroll-associated virus 3 in cabernet sauvignon vineyards
- (2016) Sarah L. MacDonald et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Toward a Reduced Reliance on Conventional Pesticides in European Agriculture
- (2016) Jay Ram Lamichhane et al. PLANT DISEASE
- Machine learning in geosciences and remote sensing
- (2016) David J. Lary et al. Geoscience Frontiers
- Wireless sensor networks for agriculture: The state-of-the-art in practice and future challenges
- (2015) Tamoghna Ojha et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- A Survey on Multisensor Fusion and Consensus Filtering for Sensor Networks
- (2015) Wangyan Li et al. DISCRETE DYNAMICS IN NATURE AND SOCIETY
- WSN-based Control System of Co2Concentration in Greenhouse
- (2015) Y.Q. Jiang et al. INTELLIGENT AUTOMATION AND SOFT COMPUTING
- Using high spatial resolution satellite imagery for mapping powdery mildew at a regional scale
- (2015) Lin Yuan et al. PRECISION AGRICULTURE
- Multimodal Data Fusion: An Overview of Methods, Challenges, and Prospects
- (2015) Dana Lahat et al. PROCEEDINGS OF THE IEEE
- Detection of early blight and late blight diseases on tomato leaves using hyperspectral imaging
- (2015) Chuanqi Xie et al. Scientific Reports
- Integrating Remotely Sensed and Meteorological Observations to Forecast Wheat Powdery Mildew at a Regional Scale
- (2014) Jingcheng Zhang et al. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
- Detection of early plant stress responses in hyperspectral images
- (2014) Jan Behmann et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- A novel methodology for the monitoring of the agricultural production process based on wireless sensor networks
- (2011) Soledad Escolar Díaz et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Mapping and identifying basal stem rot disease in oil palms in North Sumatra with QuickBird imagery
- (2010) Heri Santoso et al. PRECISION AGRICULTURE
- A multi-agent systems approach to distributed bayesian information fusion
- (2009) Gregor Pavlin et al. Information Fusion
- A Study on Greenhouse Automatic Control System Based on Wireless Sensor Network
- (2009) Dae-Heon Park et al. WIRELESS PERSONAL COMMUNICATIONS
- Spectral prediction of Phytophthora infestans infection on tomatoes using artificial neural network (ANN)
- (2008) X. Wang et al. INTERNATIONAL JOURNAL OF REMOTE SENSING
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExplorePublish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn More