Cotton is one of the world's most economically significant crops. Evaluating and monitoring
cotton crop growth play vital roles in precision agriculture. Unmanned aerial vehicle (UAV) …

Unmanned aerial vehicles (UAVs), equipped with sensors, have made a significant impact
in the field of agricultural analysis. Maize, being one of the most vital crops worldwide, is …

Agricultural production is transitioning from traditional tools to IoT-connected automation
devices. The integration of computer vision and agricultural automation is becoming closer …

Introduction Soybean pod count is one of the crucial indicators of soybean yield.
Nevertheless, due to the challenges associated with counting pods, such as crowded and …

In rice cultivation and breeding, obtaining accurate information on the quantity and spatial
distribution of rice plants is crucial. However, traditional field sampling methods can only …

Traditional palm oil production methods for evaluating fruit bunches (FFBs) are inefficient,
costly, and have limited coverage. This study evaluates the performance of various YOLO …

AgroCounters is an open-source repository for counting objects in images in the agricultural
domain by utilizing deep-learning algorithms. In this paper, we present the framework of …

The growing necessity for sustainable agriculture in the face of escalating global food
demands and climate change underscores the importance of optimizing crop water usage …

Wheat head detection and counting using deep learning techniques has gained
considerable attention in precision agriculture applications such as wheat growth …

YOLO represents the one-stage object detection also called regression-based object
detection. Object in the given input is directly classified and located instead of using the …