Different kinds of techniques are evaluated and analyzed for various classification models
for the detection of diseases of citrus fruits. This paper aims to systematically review the …

Brain tumor diagnosis at an early stage can improve the chances of successful treatment
and better patient outcomes. In the biomedical industry, non-invasive diagnostic procedures …

Sunflower is an important crop that is susceptible to various diseases, which can
significantly impact crop yield and quality. Early and accurate detection of these diseases is …

Real-world applications often involve imbalanced datasets, which have different
distributions of examples across various classes. When building a system that requires a …

Weather disturbances, difficult backgrounds, the shading of fruit and foliage, and other
elements can significantly affect automated yield estimation and picking in small target apple …

Climate stress poses a threat to the agricultural sector, which is vital for both the economy
and livelihoods in general. Quantifying its risk to food security, livelihoods, and sustainability …

Rice production has faced numerous challenges in recent years, and traditional methods
are still being used to detect rice diseases. This research project developed an automated …

Maize is one of the world's most important crops, and maize leaf diseases can have a direct
impact on maize yields. Although deep learning-based detection methods have been …

Late blight, caused by phytophthora infestans, is a devastating disease in potato production.
In severe cases, this can lead to potato crop failure. To rapidly detect potato late blight, in …

The identification of tomato leaf diseases is easily affected by complex backgrounds, small
differences between different diseases, and large differences between the same diseases …