Convolutional neural network based encoder-decoder architectures for semantic segmentation of plants
出版年份 2021 全文链接
标题
Convolutional neural network based encoder-decoder architectures for semantic segmentation of plants
作者
关键词
Plant leaf segmentation, Fig plant segmentation, Residual U-Net, SegNet, Plant semantic segmentation
出版物
Ecological Informatics
Volume 64, Issue -, Pages 101373
出版商
Elsevier BV
发表日期
2021-07-26
DOI
10.1016/j.ecoinf.2021.101373
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。- Robust index-based semantic plant/background segmentation for RGB- images
- (2020) Daniel Riehle et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Rosette plant segmentation with leaf count using orthogonal transform and deep convolutional neural network
- (2020) J. Praveen Kumar et al. MACHINE VISION AND APPLICATIONS
- A review of computer vision technologies for plant phenotyping
- (2020) Zhenbo Li et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Fig Plant Segmentation from Aerial Images Using a Deep Convolutional Encoder-Decoder Network
- (2019) Jorge Fuentes-Pacheco et al. Remote Sensing
- UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation
- (2019) Zongwei Zhou et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Joint Multi-Leaf Segmentation, Alignment, and Tracking for Fluorescence Plant Videos
- (2018) Xi Yin et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- A review of the use of convolutional neural networks in agriculture
- (2018) A. Kamilaris et al. JOURNAL OF AGRICULTURAL SCIENCE
- A review of the use of convolutional neural networks in agriculture
- (2018) A. Kamilaris et al. JOURNAL OF AGRICULTURAL SCIENCE
- Deep Learning for Plant Stress Phenotyping: Trends and Future Perspectives
- (2018) Asheesh Kumar Singh et al. TRENDS IN PLANT SCIENCE
- SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
- (2017) Vijay Badrinarayanan et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Agricultural robot dataset for plant classification, localization and mapping on sugar beet fields
- (2017) Nived Chebrolu et al. INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH
- Temporal dynamics of maize plant growth, water use, and leaf water content using automated high throughput RGB and hyperspectral imaging
- (2016) Yufeng Ge et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- A survey of image processing techniques for plant extraction and segmentation in the field
- (2016) Esmael Hamuda et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- A multi-sensor system for high throughput field phenotyping in soybean and wheat breeding
- (2016) Geng Bai et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Finely-grained annotated datasets for image-based plant phenotyping
- (2016) Massimo Minervini et al. PATTERN RECOGNITION LETTERS
- Machine Learning for High-Throughput Stress Phenotyping in Plants
- (2016) Arti Singh et al. TRENDS IN PLANT SCIENCE
- Crop feature extraction from images with probabilistic superpixel Markov random field
- (2015) Mengni Ye et al. COMPUTERS AND ELECTRONICS IN AGRICULTURE
- Leaf segmentation in plant phenotyping: a collation study
- (2015) Hanno Scharr et al. MACHINE VISION AND APPLICATIONS
- Image-based plant phenotyping with incremental learning and active contours
- (2013) Massimo Minervini et al. Ecological Informatics
- Accurate inference of shoot biomass from high-throughput images of cereal plants
- (2011) Mahmood R Golzarian et al. Plant Methods
Find the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
SearchCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now