Transfer learning strategies were used to develop a unique method in the field of medicine.
Investigation in this study suggests an ensemble technique for early brain tumor detection …

Medicinal plant recognition manually takes a lot of time and money. Moreover, to reduce
these resources, some researchers propose to implement artificial intelligence technology …

Leaf and fruit infections are the primary cause of the maximum harm to the crop, which
decreases the quality and amount of the goods. To improve the productivity of plants, the …

Medicinal plants are essential to healthcare since ancient times and are integral to
developing drugs and other medical treatments. More than 25% of medicines in developed …

The advent of cutting-edge techniques such as Computer Vision (CV) and Artificial
Intelligence (AI) have sparked a revolution in the agricultural industry, with applications …

Accurate and efficient medicinal plant image classification is of utmost importance as these
plants produce a wide variety of bioactive compounds that offer therapeutic benefits. With a …

Agriculture sector plays a major role for the growth of global economy. This is one of the
reasons why disease detection in herbs plants is vital in the agricultural area, as disease in …

Currently, artificial neural networks are experiencing a rebirth, which is primarily due to the
increase in the computing power of modern computers and the emergence of very large …

The classification of Euphorbia species is a challenging task due to their diverse growth
forms and morphological features. In this paper, we have used the transfer learning …

The paper proposes a novel approach to optimize the U-Net architecture for automated plant
phenotyping using the Big Bang Big Crunch (BBBC) algorithm. The BBBC algorithm is …