no code implementations • 3 May 2024 • Yijun Yan, Jinchang Ren, Barry Harrison, Oliver Lewis, Yinhe Li, Ping Ma
Peat, a crucial component in whisky production, imparts distinctive and irreplaceable flavours to the final product.
1 code implementation • 4 Jan 2024 • Xiaoquan Li, Stephan Weiss, Yijun Yan, Yinhe Li, Jinchang Ren, John Soraghan, Ming Gong
Understanding and identifying musical shape plays an important role in music education and performance assessment.
no code implementations • 7 Aug 2023 • Md Junayed Hasan, Eyad Elyan, Yijun Yan, Jinchang Ren, Md Mostafa Kamal Sarker
The objective of the framework is to au-tomatically identify, and crop heat loss sources caused by weak insulation, while also eliminating obstructive objects present in those images.
no code implementations • 26 Jul 2022 • Yijun Yan, Jinchang Ren, He Sun
Measuring the purity in the metal powder is critical for preserving the quality of additive manufacturing products.
no code implementations • 4 Nov 2021 • Yijun Yan, Jinchang Ren, Huan Zhao, James F. C. Windmill, Winifred Ijomah, Jesper de Wit, Justus von Freeden
Through capturing spectral data from a wide frequency range along with the spatial information, hyperspectral imaging (HSI) can detect minor differences in terms of temperature, moisture and chemical composition.
1 code implementation • IEEE Geoscience and Remote Sensing Letters 2021 • Yijun Yan, Jinchang Ren, Qiaoyuan Liu, Huimin Zhao, Haijiang Sun, Jaime Zabalza
The principal component analysis (PCA) and 2-D singular spectral analysis (2DSSA) are widely used for spectral domain and spatial domain feature extraction in hyperspectral images (HSI).
no code implementations • 15 Apr 2019 • Zihan Ye, Fan Lyu, Linyan Li, Qiming Fu, Jinchang Ren, Fuyuan Hu
First, we pre-train a Semantic Rectifying Network (SRN) to rectify semantic space with a semantic loss and a rectifying loss.
no code implementations • 9 Oct 2017 • Faxian Cao, Zhijing Yang, Jinchang Ren, Mengying Jiang, Wing-Kuen Ling
For Hyperspectral image (HSI) datasets, each class have their salient feature and classifiers classify HSI datasets according to the class's saliency features, however, there will be different salient features when use different normalization method.
no code implementations • 12 Sep 2017 • Faxian Cao, Zhijing Yang, Jinchang Ren, Wing-Kuen Ling
To tackle these two problems, in this paper, we propose a new framework for ELM based spectral-spatial classification of HSI, where probabilistic modelling with sparse representation and weighted composite features (WCF) are employed respectively to derive the op-timized output weights and extract spatial features.
no code implementations • 8 Sep 2017 • Faxian Cao, Zhijing Yang, Jinchang Ren, Wing-Kuen Ling
Although the sparse multinomial logistic regression (SMLR) has provided a useful tool for sparse classification, it suffers from inefficacy in dealing with high dimensional features and manually set initial regressor values.
no code implementations • 5 Sep 2017 • Faxian Cao, Zhijing Yang, Jinchang Ren, Mengying Jiang, Wing-Kuen Ling
As a new machine learning approach, extreme learning machine (ELM) has received wide attentions due to its good performances.