The present work proposes to evaluate, compare, and determine software alternatives that
present good detection performance and low computational cost for the plant segmentation …

Abstract Internet of Things (IoT) is an emerging technology where standalone equipments
and autonomous devices are connected to each other and users via Internet. When IoT …

The main purpose of the work is to evaluate the deep machine learning algorithms used for
the distinction between weeds and crop plants using the open database of images of the …

Weed is one of the main reasons that cause damage to the crop. While cultivating the crops,
many of the farmers are facing problems due to weed growth. The problems are the damage …

Agricultural production is critical to the economy. This is one of the reasons why disease
detection in plants is so important in agricultural settings, as plant disease is rather common …

For agricultural and farming practices to be more productive and cost-effective, it is
imperative that the implementation of new technologies such as the Internet of Things (IoT) …

Plant leaf infections are a common threat to global production in the long and short term
affecting not only many farmers but also consumers worldwide. Early detection and …

Smart agriculture is a concept that refers to a revolution in the agriculture industry that
promotes the monitoring of activities necessary to transform agricultural methods to ensure …

Nowadays, the Internet of things (IoT) plays a vital role in various sectors, including smart
cities, health care, industries, and agriculture. With the advancement of IoT and machine …

Vision-based detection and classification systems for identifying crops and weeds in
captured color images have recently being extensively researched due to the advantages …