Hyperspectral images can capture the spectral characteristics of surfaces and objects,
providing a 2-D spacial component to the spectral profiles found in a given scene. There are …

Significant advances in the field of digital image processing have been achieved in recent
years using deep learning, which has significantly exceeded previous methods. Deep …

To accurately recognize plant diseases under complex natural conditions, an improved plant
disease-recognition model based on the original YOLOv5 network model was established …

It has been noted that disease detection approaches based on deep learning are becoming
increasingly important in artificial intelligence‐based research in the field of agriculture …

Deep learning is a cutting-edge image processing method that is still relatively new but
produces reliable results. Leaf disease detection and categorization employ a variety of …

Pathogen infection has greatly reduced crop production. As the symptoms of diseases
usually appear when the plants are infected severely, rapid identification approaches are …

Fungal contamination of maize during pre and post-harvest is rampant and omnipresent.
Hyperspectral imaging (HSI) is a popular non-invasive technique for detection of fungal …

Cereals provide humans with essential nutrients, and its quality assessment has attracted
widespread attention. Infrared (IR) spectroscopy (IRS) and hyperspectral imaging (HSI), as …

The Kingdom of Saudi Arabia is considered to be one of the world leaders in olive
production accounting for about 6% of the global olive production. Given the fact that 94% of …

Identification and segregation of citrus fruit with diseases and peel blemishes are required to
preserve market value. Previously developed machine vision approaches could only …