Hyperspectral imaging technology for quality and safety evaluation of horticultural products: A review and celebration of the past 20-year progress

Y Lu, W Saeys, M Kim, Y Peng, R Lu - Postharvest Biology and Technology, 2020 - Elsevier
In the past 20 years, hyperspectral imaging has been widely investigated as an emerging,
promising technology for evaluating quality and safety of horticultural products. This …

Spoofing and countermeasures for speaker verification: A survey

Z Wu, N Evans, T Kinnunen, J Yamagishi, F Alegre… - speech …, 2015 - Elsevier
While biometric authentication has advanced significantly in recent years, evidence shows
the technology can be susceptible to malicious spoofing attacks. The research community …

Towards semi-supervised deep facial expression recognition with an adaptive confidence margin

H Li, N Wang, X Yang, X Wang… - Proceedings of the IEEE …, 2022 - openaccess.thecvf.com
Only parts of unlabeled data are selected to train models for most semi-supervised learning
methods, whose confidence scores are usually higher than the pre-defined threshold (ie, the …

Automated leaf disease detection in different crop species through image features analysis and One Class Classifiers

XE Pantazi, D Moshou, AA Tamouridou - Computers and electronics in …, 2019 - Elsevier
The presented approach demonstrates an automated way of crop disease identification on
various leaf sample images corresponding to different crop species employing Local Binary …

Adaptively learning facial expression representation via cf labels and distillation

H Li, N Wang, X Ding, X Yang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Facial expression recognition is of significant importance in criminal investigation and digital
entertainment. Under unconstrained conditions, existing expression datasets are highly …

From BoW to CNN: Two decades of texture representation for texture classification

L Liu, J Chen, P Fieguth, G Zhao, R Chellappa… - International Journal of …, 2019 - Springer
Texture is a fundamental characteristic of many types of images, and texture representation
is one of the essential and challenging problems in computer vision and pattern recognition …

[HTML][HTML] Multi-class texture analysis in colorectal cancer histology

JN Kather, CA Weis, F Bianconi, SM Melchers… - Scientific reports, 2016 - nature.com
Automatic recognition of different tissue types in histological images is an essential part in
the digital pathology toolbox. Texture analysis is commonly used to address this problem; …

Median robust extended local binary pattern for texture classification

L Liu, S Lao, PW Fieguth, Y Guo… - … on Image Processing, 2016 - ieeexplore.ieee.org
Local binary patterns (LBP) are considered among the most computationally efficient high-
performance texture features. However, the LBP method is very sensitive to image noise and …

Local binary features for texture classification: Taxonomy and experimental study

L Liu, P Fieguth, Y Guo, X Wang, M Pietikäinen - Pattern Recognition, 2017 - Elsevier
Abstract Local Binary Patterns (LBP) have emerged as one of the most prominent and
widely studied local texture descriptors. Truly a large number of LBP variants has been …

An improved YOLOv8 for foreign object debris detection with optimized architecture for small objects

J Farooq, M Muaz, K Khan Jadoon, N Aafaq… - Multimedia Tools and …, 2024 - Springer
Abstract Automated Foreign Object Debris (FOD) detection offers significant benefit to the
aviation industry by reducing human error and enabling continuous surveillance. This paper …