Analysis of Few-Shot Techniques for Fungal Plant Disease Classification and Evaluation of Clustering Capabilities Over Real Datasets

Meta-learning baselines and database for few-shot classification in agriculture

(2021) Yang Li et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Few-Shot Learning approach for plant disease classification using images taken in the field

(2020) David Argüeso et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Biomarker Localization From Deep Learning Regression Networks

(2020) Carlos Cano-Espinosa et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Review of the State of the Art of Deep Learning for Plant Diseases: A Broad Analysis and Discussion

(2020) Reem Ibrahim Hasan et al.   Plants-Basel

Deep Learning-Based Segmentation and Quantification of Cucumber Powdery Mildew Using Convolutional Neural Network

(2019) Ke Lin et al.   Frontiers in Plant Science

A low shot learning method for tea leaf’s disease identification

(2019) Gensheng Hu et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Depthwise separable convolution architectures for plant disease classification

(2019) Kamal KC et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Plant Disease Detection and Classification by Deep Learning

(2019) Saleem et al.   Plants-Basel

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

Unsupervised image translation using adversarial networks for improved plant disease recognition

(2019) Haseeb Nazki et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Deep convolutional neural networks for mobile capture device-based crop disease classification in the wild

(2018) 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

A comparative study of fine-tuning deep learning models for plant disease identification

(2018) Edna Chebet Too 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

Automated Identification of Northern Leaf Blight-Infected Maize Plants from Field Imagery Using Deep Learning

(2017) Chad DeChant et al.   PHYTOPATHOLOGY

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

(2017) Alvaro Fuentes et al.   SENSORS

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

Chemical control of plant diseases

(2013) Takashi Hirooka et al.   JOURNAL OF GENERAL PLANT PATHOLOGY

Rice diseases classification using feature selection and rule generation techniques

(2012) Santanu Phadikar et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

An image-processing based algorithm to automatically identify plant disease visual symptoms

(2008) A. Camargo et al.   BIOSYSTEMS ENGINEERING