Infrastructure development is a leading driver of forest cover loss in the tropics, resulting in a
significant decrease in biodiversity. With recent advancements in digital image processing …

The article reviews and benchmarks machine learning methods for automatic image-based
plant species recognition and proposes a novel retrieval-based method for recognition by …

This study provides a review of CNN's ensemble learning method for transfer learning by
highlighting sections such as review studies, datasets, pre-trained models, transfer learning …

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 …

Abstract For Artificial Intelligence researchers, identifying plant species from visual data has
always been a difficult issue due to a variety of difficulties in the endeavor, such as the …

The use of deep learning models for plant identification has garnered significant attention in
the research community and has yielded promising results. In this study, we evaluate the …

Plant species recognition plays an important role in agriculture, the pharmaceutical industry,
and conservation. The traditional approaches may take days and have difficulties for non …

Handwriting problems, also known as dysgraphia, are defined as a disorder or difficulty in
producing written language associated with writing mechanics. The occurrence of …

The reuse of the pre-trained deep neural network models has been found successful in
improving the classification accuracy for the plant species identification task. However, most …

Efficient and accurate plant type identification is an important foundation for biological
research. The existing traditional machine learning classification algorithms have the defects …