Xiaoping Zeng
Chongqing University
6 Papers
7 Citations
Xiaoping Zeng is an academic researcher from Chongqing University. The author has contributed to research in topics: Computer science & Bistatic radar. The author has an hindex of 2, co-authored 6 publications.
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Papers
Lung cancer detection via breath by electronic nose enhanced with a sparse group feature selection approach
Bei Liu,Huiqing Yu,Xiaoping Zeng,Dan Zhang,Juan Gong,Ling Tian,Junhui Qian,Leilei Zhao,Shuya Zhang,Ran Liu +9 more
TL;DR: An E-nose platform with a novel thermal desorption preconcentration subsystem is designed to verify whether analyzing VOCs can reliably differentiate lung cancer patients from healthy individuals and patients with benign pulmonary diseases.
57
Domain Transfer Broad Learning System for Long-Term Drift Compensation in Electronic Nose Systems
TL;DR: This paper proposes a novel unified framework called Domain Transfer Broad Learning System (DTBLS), which is the first BLS-based transfer learning framework for the problem of dataset shift existing in E-nose systems and achieves high computation efficiency due to the existence of analytical solution.
Sparse Unidirectional Domain Adaptation Algorithm for Instrumental Variation Correction of Electronic Nose Applied to Lung Cancer Detection
Bei Liu,Xiaoping Zeng,Huiqing Yu,Xiaolin Wu,Zhihong Ye,Dan Zhang,Juan Gong,Ling Tian,Junhui Qian,Leilei Zhao,Shuya Zhang,Ran Liu +11 more
TL;DR: A novel and effective two-step sparse unidirectional domain adaptation (SUDA) algorithm is proposed that is not only significantly effective for correcting instrumental variation in the two homemade lung-cancer-detection E-noses, but also demonstrates superior performance on a public E-Nose instrumental variation dataset.
9
Multi-feature Fusion Speech Emotion Recognition Based on SVM
Xiaoping Zeng,Li Dong,Guanghui Chen,Qi Dong +3 more
- 17 Jul 2020
TL;DR: A multi-feature fusion speech emotion recognition system based on Gaussian kernel nonlinear support vector machine (SVM), it is suitable for voice human-computer interaction systems.
6
High-Accuracy and Low-Complexity DOA Estimation Algorithm for Transmit-Only Diversity Bistatic MIMO Radar
TL;DR: The TOD-MUSIC algorithm can not only process correlated sources, but also reduce calculation amount by solving the DOA estimation ambiguity problem under the under-sampling and the physical properties of spectral peak is utilized to make the spectral peak more obvious.