This paper provides a review of the most recent works in machine olfaction as applied to the
identification of Chinese Herbal Medicines (CHMs). Due to the wide variety of CHMs, the …

Assessment of the earthquake-induced liquefaction potential is a critical concern in design
processes of construction projects. This study proposes a novel soft computing model with a …

In this paper, we proposed a machine vision system based on deep convolutional neural
network (DCNN) architecture for improving the accuracy of classifying three distinct groups …

Although many methods have been implemented in the past, face recognition is still an
active field of research especially after the current increased interest in security. In this …

For the process data analytics, numerous statistical methods are designed to extract
informative features to reveal latent characteristics and correlation patterns among the …

Datastream analysis aims at extracting discriminative information for classification from
continuously incoming samples. It is extremely challenging to detect novel data while …

Kernel Fisher discriminant analysis (KFDA) is a very popular learning method for the
purpose of classification. In this paper, we propose a novel learning algorithm to improve …

Sparsity preserving projection (SPP), as a widely used linear unsupervised dimensionality
reduction (DR) method, is designed to preserve the sparse reconstructive relationship of the …

Feature extraction is a crucial technique for data preprocessing in classification tasks such
as protein classification and image classification. Datasets with tree class hierarchies have …

This study proposes an image classification methodology that automatically classifies
human brain magnetic resonance (MR) images. The proposed methods contain four main …