A deep learning approach for RGB image-based powdery mildew disease detection on strawberry leaves

Effect of directional augmentation using supervised machine learning technologies: A case study of strawberry powdery mildew detection

(2020) Jaemyung Shin et al.   BIOSYSTEMS ENGINEERING

Comparing different deep learning architectures for classification of chest radiographs

(2020) Keno K. Bressem et al.   Scientific Reports

Supervised Image Classification by Scattering Transform with Application to Weed Detection in Culture Crops of High Density

(2019) Pejman Rasti et al.   Remote Sensing

Deep learning in agriculture: A survey

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

Detection of grapevine yellows symptoms in Vitis vinifera L. with artificial intelligence

(2018) Albert Cruz et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

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

(2017) Alvaro Fuentes et al.   SENSORS

Deep Learning for Image-Based Cassava Disease Detection

(2017) Amanda Ramcharan et al.   Frontiers in Plant Science

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 learning

(2015) Yann LeCun et al.   NATURE

Deep Learning-Based Classification of Hyperspectral Data

(2014) Yushi Chen et al.   IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Effect of pesticide application on soil microorganisms

(2011) Anu Kalia et al.   Archives of Agronomy and Soil Science

Conditions for Development of Powdery Mildew of Tomato Caused byOidium neolycopersici

(2008) D. Jacob et al.   PHYTOPATHOLOGY