Towards practical 2D grapevine bud detection with fully convolutional networks

Grape detection, segmentation, and tracking using deep neural networks and three-dimensional association

(2020) Thiago T. Santos et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Effects of canopy management practices on grapevine bud fruitfulness

(2020) Cassandra Collins et al.   OENO One

An adaptable approach to automated visual detection of plant organs with applications in grapevine breeding

(2019) Jonatan Grimm et al.   BIOSYSTEMS ENGINEERING

A survey on deep learning techniques for image and video semantic segmentation

(2018) Alberto Garcia-Garcia et al.   APPLIED SOFT COMPUTING

Grapevine buds detection and localization in 3D space based on Structure from Motion and 2D image classification

(2018) Carlos Ariel Díaz et al.   COMPUTERS IN INDUSTRY

ActiVis: Visual Exploration of Industry-Scale Deep Neural Network Models

(2018) Minsuk Kahng et al.   IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS

Fully Convolutional Networks for Semantic Segmentation

(2017) Evan Shelhamer et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

A survey on deep learning in medical image analysis

(2017) Geert Litjens et al.   MEDICAL IMAGE ANALYSIS

The Basis of Defoliation Effects on Reproductive Parameters in Vitis vinifera L. cv. Chardonnay Lies in the Latent Bud

(2016) P. W. Noyce et al.   AMERICAN JOURNAL OF ENOLOGY AND VITICULTURE

Grapevine Yield and Leaf Area Estimation Using Supervised Classification Methodology on RGB Images Taken under Field Conditions

(2012) Maria-Paz Diago et al.   SENSORS

Grape clusters and foliage detection algorithms for autonomous selective vineyard sprayer

(2010) Ron Berenstein et al.   Intelligent Service Robotics

A Survey on Transfer Learning

(2009) Sinno Jialin Pan et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Lessons from nearly 20 years of Precision Agriculture research, development, and adoption as a guide to its appropriate application

(2009) R. G. V. Bramley   Crop & Pasture Science