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

Toward Good Practices for Fine-Grained Maize Cultivar Identification With Filter-Specific Convolutional Activations

(2018) Hao Lu et al.   IEEE Transactions on Automation Science and Engineering

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

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

Recognition of Wheat Spike from Field Based Phenotype Platform Using Multi-Sensor Fusion and Improved Maximum Entropy Segmentation Algorithms

(2018) Chengquan Zhou et al.   Remote Sensing

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

Yield determination, interplay between major components and yield stability in a traditional and a contemporary wheat across a wide range of environments

(2017) Ariel Ferrante et al.   FIELD CROPS RESEARCH

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

Region-based colour modelling for joint crop and maize tassel segmentation

(2016) Hao Lu et al.   BIOSYSTEMS ENGINEERING

Fine-grained maize tassel trait characterization with multi-view representations

(2015) Hao Lu et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE