Coffee is regarded as the highest consumed drink around the globe and has accounted as a
major source of income in the regions where it is cultivated. To meet the coffee …

In practice, acquiring and annotating data in specialized domains can be costly, thereby
constraining the performance and applicability of deep learning. Utilizing generative models …

In the era of advancing artificial intelligence (AI), its application in agriculture has become
increasingly pivotal. This study explores the integration of AI for the discriminative …

Maize is an important crop cultivated in Sub-Saharan Africa, essential for food security.
However, its cultivation faces significant challenges due to debilitating diseases such as …

Researchers have designed various models trained on public or private datasets for plant
disease detection to help farmers remedy crop yield losses on their farms due to plant …

Cauliflower cultivation plays a pivotal role in the Indian Subcontinent's winter crop**
landscape, contributing significantly to both agricultural output, economy and public health …

Plant diseases are increasingly becoming a serious threat to food security as well as
sustainable agriculture sets. Traditional methods for detecting crop diseases, especially in …

In order to detect rice false smut quickly and accurately, a lightweight false smut detection
model, YOLOv8n-MBS, was proposed in this study. The model introduces the C2f_MSEC …

Plant pest and disease management, especially in the early stages of infestation, is a critical
challenge that poses significant threats and has potential to devastate agricultural crops …

Advances in deep learning (DL) models and next-generation edge devices enable real-time
image classification, driving a transition from the traditional, purely cloud-centric IoT …