A traditional deep neural network-based classifier assumes that only training classes appear
during testing in closed-world settings. In most real-world applications, an open-set …

The exact and unfailing categorization of medicinal plants exceeds the capabilities of the
average individual because it necessitates in-depth subject expertise and physical detection …

With artificial intelligence to promote the rapid development of precision agriculture, the
management and detection of agricultural resources through computer vision and deep …

Taxonomy language is challenging to comprehend and automated knowledge is required to
identify the plant species. The study focused on developing an improved deep neural …

Driven by significant a dvancements in computer vision, image classification h as e ntered ar
evolutionary phase with improved accuracy and prospective applications. Nowadays …

In this research, TensorFlow, a powerful deep learning toolkit, is utilized in conjunction with
the Python programming language to conduct a comprehensive analysis of plant names and …

Plant classification using deep learning models has witnessed significant progress in recent
years, contributing to advancements in agriculture, environmental monitoring, and …

Agriculture is a significant contributor in the global economy, as it is the key source of
income for about 50% of the global population. Statistics reveal that in the financial year …

Chilli is one of the important spices and commonly adulterated for the economic gain.
Manual identification is time-taking, expensive and needs experience expert which are often …

In this study, four plant identification mobile apps, namely LeafSnap, PictureThis, Pl@ ntNet,
and PlantSnap, were tried by volunteer participants who are students, teachers, and plant …