Rice Plant Counting, Locating, and Sizing Method Based on High-Throughput UAV RGB Images.

Rice plant counting is crucial for many applications in rice production, such as yield estimation, growth diagnosis, disaster loss assessment, etc. Currently, rice counting still heavily relies on tedious and time-consuming manual operation. To alleviate the workload of rice counting, we employed an UAV (unmanned aerial vehicle) to collect the RGB images of the paddy field.

Decoupled Two-Stage Crowd Counting and Beyond.

One of appealing approaches to counting dense objects, such as crowd, is density map estimation. Density maps, however, present ambiguous appearance cues in congested scenes, rendering infeasibility in identifying individuals and difficulties in diagnosing errors. Inspired by an observation that counting can be interpreted as a two-stage process, i.

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

Background: Grain yield of wheat is greatly associated with the population of wheat spikes, i.e., .