Insect pest detection and monitoring are vital in an agricultural crop to help prevent losses
and be more precise and sustainable regarding the consequent actions to be taken. Deep …

Drone detection is a significant research topic due to the potential security threats posed by
the misuse of drones in both civilian and military domains. However, traditional drone …

The monitoring of the tassel number and tasseling time reflects the maize growth and is
necessary for crop management. However, it mainly depends on field observations, which is …

In the evolving landscape of precision agriculture, the integration of remote pest traps with
deep learning technologies marks a critical step forward in remote pest detection, with the …

Face mask detection is a technological application that employs computer vision
methodologies to ascertain the presence or absence of a face mask on an individual …

Abstract Integrated Pest Management (IPM) is an essential approach used in smart
agriculture to manage pest populations and sustainably optimize crop production. One of the …

Introduction Deep learning (DL) is a core constituent for building an object detection system
and provides a variety of algorithms to be used in a variety of applications. In agriculture …

The primary challenges in tea production under multiple stress exposures have negatively
affected its global market sustainability, so introducing an infield fast technique for …

Pests significantly negatively affect product yield and quality in agricultural production.
Agricultural producers may not accurately identify pests and signs of pest damage. Thus …

The widespread of Pomacea canaliculata, a new “killer” in rice fields, may threaten the
productivity and quality of rice. Therefore, kee** an eye on it is crucial for food security …