[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Zhou et al., 2023 - Google Patents

Analyzing nitrogen effects on rice panicle development by panicle detection and time-series tracking

Zhou et al., 2023

View PDF @Full View
Document ID
8704931046769295145
Author
Zhou Q
Guo W
Chen N
Wang Z
Li G
Ding Y
Ninomiya S
Mu Y
Publication year
Publication venue
Plant Phenomics

External Links

Snippet

Detailed observation of the phenotypic changes in rice panicle substantially helps us to understand the yield formation. In recent studies, phenotyping of rice panicles during the heading–flowering stage still lacks comprehensive analysis, especially of panicle …
Continue reading at spj.science.org (PDF) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G06F17/30587Details of specialised database models
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30244Information retrieval; Database structures therefor; File system structures therefor in image databases
    • G06F17/30247Information retrieval; Database structures therefor; File system structures therefor in image databases based on features automatically derived from the image data
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00624Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G06K9/0063Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas
    • G06K9/00657Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas of vegetation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G06F17/30386Retrieval requests
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06K9/6232Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
    • G06K9/6247Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46Extraction of features or characteristics of the image
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6267Classification techniques
    • G06K9/6268Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10Complex mathematical operations
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/40Analysis of texture
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00127Acquiring and recognising microscopic objects, e.g. biological cells and cellular parts
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details

Similar Documents

Publication Publication Date Title
Chen et al. Weed detection in sesame fields using a YOLO model with an enhanced attention mechanism and feature fusion
Zhou et al. Analyzing nitrogen effects on rice panicle development by panicle detection and time-series tracking
Li et al. SPM-IS: An auto-algorithm to acquire a mature soybean phenotype based on instance segmentation
Liu et al. High-throughput rice density estimation from transplantation to tillering stages using deep networks
Sun et al. Remote estimation of grafted apple tree trunk diameter in modern orchard with RGB and point cloud based on SOLOv2
Huang et al. Early mapping of winter wheat in Henan province of China using time series of Sentinel-2 data
He et al. Recognition of soybean pods and yield prediction based on improved deep learning model
Miao et al. Classification of farmland images based on color features
Patel et al. Deep learning-based plant organ segmentation and phenotyping of sorghum plants using LiDAR point cloud
Díaz et al. Grapevine buds detection and localization in 3D space based on structure from motion and 2D image classification
Wang et al. TBC-YOLOv7: a refined YOLOv7-based algorithm for tea bud grading detection
Wang et al. DFSP: A fast and automatic distance field-based stem-leaf segmentation pipeline for point cloud of maize shoot
Mirnezami et al. Detection of the progression of anthesis in field-grown maize tassels: a case study
Khaki et al. High-throughput image-based plant stand count estimation using convolutional neural networks
Zhang et al. Automatic non-destructive multiple lettuce traits prediction based on DeepLabV3+
Li et al. Soybean leaf estimation based on RGB images and machine learning methods
Maheswari et al. Intelligent yield estimation for tomato crop using SegNet with VGG19 architecture
Li et al. CSNet: A count-supervised network via multiscale MLP-Mixer for wheat ear counting
Yu et al. Time-series field phenotyping of soybean growth analysis by combining multimodal deep learning and dynamic modeling
Carlier et al. Wheat ear segmentation based on a multisensor system and superpixel classification
Zhu et al. Exploring soybean flower and pod variation patterns during reproductive period based on fusion deep learning
Sun et al. Accurate rice grain counting in natural morphology: a method based on image classification and object detection
Lin et al. A framework for single-panicle litchi flower counting by regression with multitask learning
CN102621075B (en) Method for automatically detecting rice heading stage
Kokate et al. Classification of tomato leaf disease using a custom convolutional neural network