A deep learning approach to measure stress level in plants due to Nitrogen deficiency

Identification and Classification of Maize Drought Stress Using Deep Convolutional Neural Network

(2019) Jiangyong An et al.   Symmetry-Basel

Automated analysis of visual leaf shape features for plant classification

(2019) G. Saleem et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Plant disease identification from individual lesions and spots using deep learning

(2019) Jayme Garcia Arnal Barbedo   BIOSYSTEMS ENGINEERING

Seed-per-pod estimation for plant breeding using deep learning

(2018) L.C. Uzal et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Deep learning in agriculture: A survey

(2018) Andreas Kamilaris et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Multi-Organ Plant Classification Based on Convolutional and Recurrent Neural Networks

(2018) Sue Han Lee et al.   IEEE TRANSACTIONS ON IMAGE PROCESSING

Close-range hyperspectral image analysis for the early detection of stress responses in individual plants in a high-throughput phenotyping platform

(2018) Mohd Shahrimie Mohd Asaari et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

An explainable deep machine vision framework for plant stress phenotyping

(2018) Sambuddha Ghosal et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Identification of Maize Leaf Diseases Using Improved Deep Convolutional Neural Networks

(2018) Xihai Zhang et al.   IEEE Access

Plant Leaf Classification Using GIST Texture Features

(2018) Habibollah Asghari et al.   IET Computer Vision

Ear density estimation from high resolution RGB imagery using deep learning technique

(2018) Simon Madec et al.   AGRICULTURAL AND FOREST METEOROLOGY

A novel computer vision based neutrosophic approach for leaf disease identification and classification

(2018) Gittaly Dhingra et al.   MEASUREMENT

Imaging analysis of chlorophyll fluorescence induction for monitoring plant water and nitrogen treatments

(2018) Chunyan Zhou et al.   MEASUREMENT

fvUnderwater sea cucumber identification based on Principal Component Analysis and Support Vector Machine

(2018) Xi Qiao et al.   MEASUREMENT

A survey on deep learning in medical image analysis

(2017) Geert Litjens et al.   MEDICAL IMAGE ANALYSIS

How Deep Learning Extracts and Learns Leaf Features for Plant Classification

(2017) Sue Han Lee et al.   PATTERN RECOGNITION

A real-time phenotyping framework using machine learning for plant stress severity rating in soybean

(2017) Hsiang Sing Naik et al.   Plant Methods

Deep Count: Fruit Counting Based on Deep Simulated Learning

(2017) et al.   SENSORS

Deep Learning for Plant Identification in Natural Environment

(2017) Yu Sun et al.   Computational Intelligence and Neuroscience

Genome-wide transcriptome analysis of soybean primary root under varying water-deficit conditions

(2016) Li Song et al.   BMC GENOMICS

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

Machine Learning for High-Throughput Stress Phenotyping in Plants

(2016) Arti Singh et al.   TRENDS IN PLANT SCIENCE

Image Analysis: The New Bottleneck in Plant Phenotyping [Applications Corner]

(2015) Massimo Minervini et al.   IEEE SIGNAL PROCESSING MAGAZINE

Deep learning

(2015) Yann LeCun et al.   NATURE

Dissecting spatiotemporal biomass accumulation in barley under different water regimes using high-throughput image analysis

(2015) Kerstin Neumann et al.   PLANT CELL AND ENVIRONMENT

Automated phenotyping of plant shoots using imaging methods for analysis of plant stress responses – a review

(2015) Jan F Humplík et al.   Plant Methods