Abstract: Identifying medicinal plants is crucial in herbal medicine, pharmaceutical research, and plant taxonomy. Conventional manual classification techniques tend to be errorprone and ...
Abstract: Plant diseases represent a significant danger to agricultural output, frequently resulting in considerable crop losses. Timely and precise detection of such diseases is essential to ...
Abstract: There has been a 37% yearly decrease in rice yields as a result of rice plant diseases. It might happen mostly as a result of not knowing how to identify and treat diseases that affect rice ...
Abstract: Tomato leaf diseases are a significant threat to crop yield and agricultural productivity across the world. Conventional detection methods rely on human eye ...
Abstract: Sugarcane is an important agricultural commodity in Indonesia economy, serving as the main raw material for sugar production. Therefore, it is crucial for farmers to perform early disease ...
Abstract: This work introduces a deep learning method for cotton plant disease classification with leaf images. A good-balanced dataset of 9,000 labeled images covering nine classes—Aphids, Bacterial ...
Abstract: Accurate early diagnosis of plant diseases must be ensured for proper agricultural output and minimizing losses economically. Hybrid optimization using deep learning is utilized by the ...
Abstract: Early detection of plant disease is useful in reducing its rapid spread; however similar visual appearances of different plant diseases make it a challenging problem. In the proposed ...
Abstract: The agriculture industry faces significant challenges in maintaining sustainable plant growth while combating diseases that threaten crops. Traditional disease prevention methods rely on ...
CNN’s Harry Enten breaks down the numbers. Republican signals support for Trump impeachment 17 college basketball players charged in point-shaving scheme: Indictment I asked 3 restaurant pros to name ...