Agriculture plays a vital role in the economic growth of any country. With the increase of
population, frequent changes in climatic conditions and limited resources, it becomes a …

In the modern era, deep learning techniques have emerged as powerful tools in image
recognition. Convolutional Neural Networks, one of the deep learning tools, have attained …

Potato disease management plays a valuable role in the agriculture field as it might cause a
significant loss in crops production. Therefore, timely recognition and classification of potato …

Plant disease computerization in agriculture areas an important for every country, as the
population rate increases the demand for food supply also increases. Today, the significant …

Deep learning (DL) is a robust data-analysis and image-processing technique that has
shown great promise in the agricultural sector. In this study, 129 papers that are based on …

Highlights•A method for increasing size and diversity of plant disease image datasets is
proposed.•Diagnosis is based on image classification for individual lesions and …

Rapid improvements in deep learning (DL) techniques have made it possible to detect and
recognize objects from images. DL approaches have recently entered various agricultural …

The problem of automatic recognition of plant diseases has been historically based on
conventional machine learning techniques such as Support Vector Machines, Multilayer …

Deep learning techniques, and in particular Convolutional Neural Networks (CNNs), have
led to significant progress in image processing. Since 2016, many applications for the …

In the field of agricultural information, the automatic identification and diagnosis of maize leaf
diseases is highly desired. To improve the identification accuracy of maize leaf diseases and …