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

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

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

Development of a sweet pepper harvesting robot

(2020) Boaz Arad et al.   Journal of Field Robotics

YOLO-Tomato: A Robust Algorithm for Tomato Detection Based on YOLOv3

(2020) Guoxu Liu et al.   SENSORS

Recognition and Localization Methods for Vision-Based Fruit Picking Robots: A Review

(2020) Yunchao Tang et al.   Frontiers in Plant Science

Three-dimensional perception of orchard banana central stock enhanced by adaptive multi-vision technology

(2020) Mingyou Chen et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Fast and accurate detection of kiwifruit in orchard using improved YOLOv3-tiny model

(2020) Longsheng Fu et al.   PRECISION AGRICULTURE

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

(2019) Yang-Yang Zheng et al.   SENSORS

Fruit detection in natural environment using partial shape matching and probabilistic Hough transform

(2019) Guichao Lin et al.   PRECISION AGRICULTURE

Detection and counting of flowers on apple trees for better chemical thinning decisions

(2019) Guy Farjon et al.   PRECISION AGRICULTURE

Deep learning based banana plant detection and counting using high-resolution red-green-blue (RGB) images collected from unmanned aerial vehicle (UAV)

(2019) Bipul Neupane et al.   PLoS One

Deep learning for noninvasive classification of clustered horticultural crops – A case for banana fruit tiers

(2019) Tuan-Tang Le et al.   POSTHARVEST BIOLOGY AND TECHNOLOGY

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

(2019) Haipeng Xiong et al.   Plant Methods

Machine vision assessment of mango orchard flowering

(2018) Zhenglin Wang et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Apple flower detection using deep convolutional networks

(2018) Philipe A. Dias et al.   COMPUTERS IN INDUSTRY

Wheat ear counting in-field conditions: high throughput and low-cost approach using RGB images

(2018) Jose A. Fernandez-Gallego et al.   Plant Methods

Wheat Ears Counting in Field Conditions Based on Multi-Feature Optimization and TWSVM

(2018) Chengquan Zhou et al.   Frontiers in Plant Science

Ear density estimation from high resolution RGB imagery using deep learning technique

(2018) Simon Madec et al.   AGRICULTURAL AND FOREST METEOROLOGY

Detection and analysis of wheat spikes using Convolutional Neural Networks

(2018) Md Mehedi Hasan et al.   Plant Methods

Image Segmentation for Fruit Detection and Yield Estimation in Apple Orchards

(2017) Suchet Bargoti et al.   Journal of Field Robotics

TasselNet: counting maize tassels in the wild via local counts regression network

(2017) Hao Lu et al.   Plant Methods

Detecting spikes of wheat plants using neural networks with Laws texture energy

(2017) Li Qiongyan et al.   Plant Methods

Deep Count: Fruit Counting Based on Deep Simulated Learning

(2017) et al.   SENSORS

Finely-grained annotated datasets for image-based plant phenotyping

(2016) Massimo Minervini et al.   PATTERN RECOGNITION LETTERS

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

Automated image-processing for counting seedlings in a wheat field

(2015) Tao Liu et al.   PRECISION AGRICULTURE

Automated Visual Yield Estimation in Vineyards

(2014) Stephen Nuske et al.   Journal of Field Robotics

Articulated Human Detection with Flexible Mixtures of Parts

(2012) Yi Yang 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

Quantifying bunch weights of the East African Highland bananas (Musa spp. AAA-EA) using non-destructive field observations

(2009) L.W.I. Wairegi et al.   SCIENTIA HORTICULTURAE