Object detection in agricultural contexts: A multiple resolution benchmark and comparison to human

Parts-per-Object Count in Agricultural Images: Solving Phenotyping Problems via a Single Deep Neural Network

(2021) Faina Khoroshevsky et al.   Remote Sensing

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

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

Plant Phenotyping Research Trends, a Science Mapping Approach

(2019) Corrado Costa et al.   Frontiers in Plant Science

CropDeep: The Crop Vision Dataset for Deep-Learning-Based Classification and Detection in Precision Agriculture

(2019) Yang-Yang Zheng et al.   SENSORS

TasselNetv2: in-field counting of wheat spikes with context-augmented local regression networks

(2019) Haipeng Xiong et al.   Plant Methods

Deep learning in agriculture: A survey

(2018) Andreas Kamilaris 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

Adaptive thresholding with fusion using a RGBD sensor for red sweet-pepper detection

(2016) Efi Vitzrabin et al.   BIOSYSTEMS ENGINEERING

A procedure for estimating the number of green mature apples in night-time orchard images using light distribution and its application to yield estimation

(2016) Raphael Linker   PRECISION AGRICULTURE

DeepFruits: A Fruit Detection System Using Deep Neural Networks

(2016) Inkyu Sa et al.   SENSORS

Sensors and systems for fruit detection and localization: A review

(2015) A. Gongal et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Fast Feature Pyramids for Object Detection

(2014) Piotr Dollar et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Grape clusters and foliage detection algorithms for autonomous selective vineyard sprayer

(2010) Ron Berenstein et al.   Intelligent Service Robotics

The Pascal Visual Object Classes (VOC) Challenge

(2009) Mark Everingham et al.   INTERNATIONAL JOURNAL OF COMPUTER VISION