Deep Learning model of sequential image classifier for crop disease detection in plantain tree cultivation

Beans Leaf Diseases Classification Using MobileNet Models

(2022) Elhoucine Elfatimi et al.   IEEE Access

A Lightweight Attention-Based Convolutional Neural Networks for Tomato Leaf Disease Classification

(2022) Anil Bhujel et al.   Agriculture-Basel

Crop pest recognition using attention-embedded lightweight network under field conditions

(2021) Junde Chen et al.   APPLIED ENTOMOLOGY AND ZOOLOGY

Identifying crop diseases using attention embedded MobileNet-V2 model

(2021) Junde Chen et al.   APPLIED SOFT COMPUTING

Deep Neural Network Compression for Plant Disease Recognition

(2021) Ruiqing Wang et al.   Symmetry-Basel

Deep learning for classification and severity estimation of coffee leaf biotic stress

(2020) José G.M. Esgario et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Towards weeds identification assistance through transfer learning

(2020) Borja Espejo-Garcia et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Graph weeds net: A graph-based deep learning method for weed recognition

(2020) Kun Hu et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Using deep transfer learning for image-based plant disease identification

(2020) Junde Chen et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Instance segmentation for the fine detection of crop and weed plants by precision agricultural robots

(2020) Julien Champ et al.   Applications in Plant Sciences

Attention embedded lightweight network for maize disease recognition

(2020) Junde Chen et al.   PLANT PATHOLOGY

A study on plant recognition using conventional image processing and deep learning approaches

(2019) S. Anubha Pearline et al.   JOURNAL OF INTELLIGENT & FUZZY SYSTEMS

Potato Virus Y Detection in Seed Potatoes Using Deep Learning on Hyperspectral Images

(2019) Gerrit Polder et al.   Frontiers in Plant Science

Deep learning for image-based weed detection in turfgrass

(2019) Jialin Yu et al.   EUROPEAN JOURNAL OF AGRONOMY

Crop Yield Prediction Using Deep Neural Networks

(2019) Saeed Khaki et al.   Frontiers in Plant Science

Automated machine learning for identification of pest aphid species (Hemiptera: Aphididae)

(2019) Masayuki Hayashi et al.   APPLIED ENTOMOLOGY AND ZOOLOGY

Crop pest classification based on deep convolutional neural network and transfer learning

(2019) K. Thenmozhi et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Deep Learning for Image Sequence Classification of Astronomical Events

(2019) Rodrigo Carrasco-Davis et al.   PUBLICATIONS OF THE ASTRONOMICAL SOCIETY OF THE PACIFIC

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

Deep learning models for plant disease detection and diagnosis

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

Big data and machine learning for crop protection

(2018) Ryan H.L. Ip et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

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

Automatic in-trap pest detection using deep learning for pheromone-based Dendroctonus valens monitoring

(2018) Yu Sun et al.   BIOSYSTEMS ENGINEERING

PENYEK: Automated brown planthopper detection from imperfect sticky pad images using deep convolutional neural network

(2018) Azree Nazri et al.   PLoS One

Deep Learning Classification of Land Cover and Crop Types Using Remote Sensing Data

(2017) Nataliia Kussul et al.   IEEE Geoscience and Remote Sensing Letters

Long-Term Recurrent Convolutional Networks for Visual Recognition and Description

(2017) Jeff Donahue et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

A Robust Deep-Learning-Based Detector for Real-Time Tomato Plant Diseases and Pests Recognition

(2017) Alvaro Fuentes et al.   SENSORS

Combination of image processing and artificial neural networks as a novel approach for the identification of Bemisia tabaci and Frankliniella occidentalis on sticky traps in greenhouse agriculture

(2016) Karlos Espinoza et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Using Deep Learning for Image-Based Plant Disease Detection

(2016) Sharada P. Mohanty et al.   Frontiers in Plant Science

Deep Neural Networks Based Recognition of Plant Diseases by Leaf Image Classification

(2016) Srdjan Sladojevic et al.   Computational Intelligence and Neuroscience

Automatic identification and counting of small size pests in greenhouse conditions with low computational cost

(2015) Chunlei Xia et al.   Ecological Informatics

Detection of small-sized insect pest in greenhouses based on multifractal analysis

(2015) Yan Li et al.   OPTIK

Plant species identification using digital morphometrics: A review

(2012) James S. Cope et al.   EXPERT SYSTEMS WITH APPLICATIONS