Satellite communication offers the prospect of service continuity over uncovered and under-
covered areas, service ubiquity, and service scalability. However, several challenges must …

The past decade has witnessed many great successes of machine learning (ML) and deep
learning (DL) applications in agricultural systems, including weed control, plant disease …

Abstract The Global Wheat Head Detection (GWHD) dataset was created in 2020 and has
assembled 193,634 labelled wheat heads from 4700 RGB images acquired from various …

Recent deep learning methods have allowed important steps forward in the automatic
detection of wheat ears in the field. Nevertheless, it was still lacking a method able to both …

Wheat is one of the most vital crops around the globe. Due to wheat mosaic virus disease,
there are a huge amount of yield quality losses. The mosaic virus is transmitted through curl …

Detection and counting of wheat heads are crucial for wheat yield estimation. To address the
issues of overlapping and small volumes of wheat heads on complex backgrounds, this …

Early grapevine yield forecasting at satisfactory accuracy is among the major trends in
precision viticulture research. Conventionally, yield is estimated manually through …

The yield of rice crops is strongly correlated to the number of panicles per unit area.
Computer vision techniques have been utilized in previous studies to count the number of …

Addressing biases in AI models is crucial for ensuring fair and accurate predictions.
However, obtaining large, unbiased datasets for training can be challenging. This paper …

Grain count is an important trait in sorghum because it is highly correlated to the potential
yield. By accurately phenotyping the number of grains per panicle, farmers and agronomists …