The aim of the proposed work is to review the various AI techniques (fuzzy logic (FL),
artificial neural network (ANN), genetic algorithm (GA), particle swarm optimization (PSO) …

In the recent decade, high-throughput plant phenotyping techniques, which combine
noninvasive image analysis and machine learning, have been successfully applied to …

Due to the integration of artificial intelligence with sensors and devices utilized by Internet of
Things technology, the interest in automation systems has increased. One of the common …

Plant stress reduction research has advanced significantly with the use of Artificial
Intelligence (AI) techniques, such as machine learning and deep learning. This is a …

Water stress in plants is due to water deficiency probably caused by soil salinity and
drought. Water stress in crops leads to loss in agricultural production that results in food …

Plant health conditions can be identified destructively and non-destructively. However, the
destructive method was considered ineffective due to human error because of repeated …

We propose a novel hybrid classifier for hyperspectral images using Bat Algorithm (BA) to
optimize the architecture of a Convolutional Neural Network (CNN). BA is applied by …

Emotion recognition via Electroencephalogram (EEG) has gained considerable attention in
the recent years due to its objective and naturalistic response to the emotional stimulus …

This paper proposes a new approach to improve weak supervised classification of deep
CNN architectures based on data augmentation by integrating Grey Wolf Optimizer (GWO) …

Rainfed crops rarely include the application of phytosanitary products due to the high cost of
their application and the reduced rentability of crops. Nonetheless, if diseases are early …