Identification of Apple Tree Leaf Diseases Based on Deep Learning Models

Apple Leaf Disease Identification Through Region-of-Interest-Aware Deep Convolutional Neural Network

(2020) Hee-Jin Yu et al.   JOURNAL OF IMAGING SCIENCE AND TECHNOLOGY

PM2.5 Prediction Based on Random Forest, XGBoost, and Deep Learning Using Multisource Remote Sensing Data

(2019) Mehdi Zamani Joharestani et al.   Atmosphere

Plant disease identification using explainable 3D deep learning on hyperspectral images

(2019) Koushik Nagasubramanian et al.   Plant Methods

Deep Learning for Soil and Crop Segmentation from Remotely Sensed Data

(2019) Jack Dyson et al.   Remote Sensing

Convolutional Neural Networks for the Automatic Identification of Plant Diseases

(2019) Justine Boulent et al.   Frontiers in Plant Science

Research on deep learning in apple leaf disease recognition

(2019) Yong Zhong 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

Very Deep Convolutional Neural Networks for Complex Land Cover Mapping Using Multispectral Remote Sensing Imagery

(2018) Masoud Mahdianpari et al.   Remote Sensing

A survey of deep neural network architectures and their applications

(2017) Weibo Liu et al.   NEUROCOMPUTING

Towards better exploiting convolutional neural networks for remote sensing scene classification

(2017) Keiller Nogueira et al.   PATTERN RECOGNITION

Identification of Apple Leaf Diseases Based on Deep Convolutional Neural Networks

(2017) Bin Liu et al.   Symmetry-Basel

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

Identification of Alfalfa Leaf Diseases Using Image Recognition Technology

(2016) Feng Qin et al.   PLoS One

Spectral analysis of winter wheat leaves for detection and differentiation of diseases and insects

(2013) Lin Yuan et al.   FIELD CROPS RESEARCH

Predicting the spread of postharvest disease in stored fruit, with application to apples

(2013) M. Dutot et al.   POSTHARVEST BIOLOGY AND TECHNOLOGY

Development of spectral indices for detecting and identifying plant diseases

(2012) A.-K. Mahlein et al.   REMOTE SENSING OF ENVIRONMENT