Abstract In Machine Learning (ML), Feature Selection (FS) plays a crucial part in reducing
data's dimensionality and enhancing any proposed framework's performance. However, in …

A hyperspectral imaging sensor collects detailed spectral responses from ground objects
using hundreds of narrow bands; this technology is used in many real-world applications …

A deep-learning architecture based on Convolutional Neural Networks (CNN) and a cost-
effective computer vision module were used to detect defective apples on a four-line fruit …

The analysis of infrared spectroscopy of substances is a non-invasive measurement
technique that can be used in analytics. Although the main objective of this study is to …

Detection of foreign objects is crucial for quantitative image analysis in numerous food
quality and safety inspection applications. Rapid detection of foreign objects in walnuts …

The innovation in science and technical knowledge has prompted an enormous amount of
information for the agrarian sector. Machine learning has risen with massive processing …

This article proposes a multiscale spectral features graph fusion (MSFGF) method for
selecting proper hyperspectral bands. The MSFGF regards that the selected bands should …

The recovery and recycling of textile waste is becoming urgent since textiles are generating
more and more waste. In one year, about 92 million tons of textile waste are produced and …

This paper deals with the problem of integrating the most suitable feature selection methods
for a given problem in order to achieve the best feature order. A new, adaptive and hybrid …

Cotton is an important source of natural fiber around the world. Cotton lint, however, could
be contaminated by various types of foreign matter (FM) during harvesting and processing …