Quantitative phenotyping and evaluation for lettuce leaves of multiple semantic components

Greenhouse-based vegetable high-throughput phenotyping platform and trait evaluation for large-scale lettuces

(2021) Jianjun Du et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Applications of deep-learning approaches in horticultural research: a review

(2021) Biyun Yang et al.   Horticulture Research

Image phenotyping of lettuce germplasm with genetically diverse carotenoid levels

(2020) Gabriel Mascarenhas Maciel et al.   BRAGANTIA

Growth monitoring of greenhouse lettuce based on a convolutional neural network

(2020) Lingxian Zhang et al.   Horticulture Research

Training instance segmentation neural network with synthetic datasets for crop seed phenotyping

(2020) Yosuke Toda et al.   Communications Biology

Automatic Hierarchy Classification in Venation Networks using Directional Morphological Filtering for Hierarchical Structure Traits Extraction

(2019) Yangjing Gan et al.   COMPUTATIONAL BIOLOGY AND CHEMISTRY

Characterization of four polymorphic genes controlling red leaf color in lettuce that have undergone disruptive selection since domestication

(2019) Wenqing Su et al.   PLANT BIOTECHNOLOGY JOURNAL

Combining computer vision and deep learning to enable ultra-scale aerial phenotyping and precision agriculture: A case study of lettuce production

(2019) Alan Bauer et al.   Horticulture Research

Image phenotyping of inbred red lettuce lines with genetic diversity regarding carotenoid levels

(2019) Gabriel Mascarenhas Maciel et al.   International Journal of Applied Earth Observation and Geoinformation

Crop Phenomics: Current Status and Perspectives

(2019) Chunjiang Zhao et al.   Frontiers in Plant Science

RootNav 2.0: Deep learning for automatic navigation of complex plant root architectures

(2019) Robail Yasrab et al.   GigaScience

Deep learning models for plant disease detection and diagnosis

(2018) Konstantinos P. Ferentinos   COMPUTERS AND ELECTRONICS IN AGRICULTURE

How Deep Learning Extracts and Learns Leaf Features for Plant Classification

(2017) Sue Han Lee et al.   PATTERN RECOGNITION

PYM: a new, affordable, image-based method using a Raspberry Pi to phenotype plant leaf area in a wide diversity of environments

(2017) Benoît Valle et al.   Plant Methods

Finely-grained annotated datasets for image-based plant phenotyping

(2016) Massimo Minervini et al.   PATTERN RECOGNITION LETTERS

High-throughput phenotyping of plant resistance to aphids by automated video tracking

(2015) Karen J Kloth et al.   Plant Methods

Detection of decay in fresh-cut lettuce using hyperspectral imaging and chlorophyll fluorescence imaging

(2015) Ivan Simko et al.   POSTHARVEST BIOLOGY AND TECHNOLOGY

Leaf development and morphogenesis

(2014) M. Bar et al.   DEVELOPMENT

Automatic classification of legumes using leaf vein image features

(2013) Mónica G. Larese et al.   PATTERN RECOGNITION

Delivering high-resolution landmarks using inkjet micropatterning for spatial monitoring of leaf expansion

(2013) Lisheng Wang et al.   Plant Methods

NIH Image to ImageJ: 25 years of image analysis

(2012) Caroline A Schneider et al.   NATURE METHODS

X-ray imaging of leaf venation networks

(2012) Benjamin Blonder et al.   NEW PHYTOLOGIST

Quantifying leaf venation patterns: two-dimensional maps

(2008) Anne-Gaëlle Rolland-Lagan et al.   PLANT JOURNAL