Advances in computing technology have fostered the development of new and powerful
deep learning (DL) techniques, which have demonstrated promising results in a wide range …

Abstract Analysis of evidence is a challenge. Crime scene materials are complex, diverse,
sometimes of an unknown nature. Forensic science provides the most critical applications …

This study aimed to achieve the rapid evaluation of moisture, ash and protein of sweet
potato simultaneously by near-infrared (NIR) hyperspectral imaging (900–1700 nm) …

Deep learning based methods have made great progress in hyperspectral image
classification. However, training a deep learning model often requires a large number of …

This review paper covers the forensic-relevant literature for the analysis and detection of
explosives and explosives residues from 2016-2019 as a part of the 19 th Interpol …

Deep convolutional neural networks (CNNs) are widely used in hyperspectral image (HSI)
classification. However, the most successful CNN architectures are handcrafted, which need …

Hyperspectral image (HSI) analysis generally suffers from issues such as high
dimensionality, imbalanced sample sets for different classes, and the choice of classifiers for …

Carious is a global chronic disease; 2 billion people and 520 million children suffer from
permanent and primary teeth caries respectively. Early caries detection via precise, non …

Explosive detection is crucial for public safety and confidence. Among various solutions for
this purpose, hyperspectral imaging differs from its alternatives with its detection capability …

Instant detection of explosive material is highly appreciated for counterterrorism activity and
homeland security. Nitro group (high energy rich bond) is responsible for explosive …